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Viewpoint: service marketing research priorities

Journal of Services Marketing

ISSN : 0887-6045

Article publication date: 3 April 2020

Issue publication date: 19 June 2020

This paper aims to emphasize two key research priorities central to the domain of service marketing.

Design/methodology/approach

Reflections based on conceptual analysis of the current level of knowledge of service as an offering and of the nature of service marketing in the literature.

It is observed that research into marketing and into service as an object of marketing, or as an offering, has been neglected for two decades and more. It is also shown that to restore its credibility, marketing needs to be reinvented. Furthermore, the point is made that if a proper understanding of service as an object of, for example, innovation, design, branding and development is lacking, or even only implicitly present, valid research into those and other important topics is at risk.

Research limitations/implications

This paper discusses two neglected topics within the domain of service research. Other important areas of future research are not covered. However, the paper offers directions for service marketing research fundamental to the development of the discipline.

Originality/value

In earlier discussions of service and service marketing research priorities, the observation that service and marketing are neglected topics that need to be studied and further developed has not been made. The paper emphasizes that service marketing research also needs to return to its roots and suggests possible directions for future research.

Service delivery
Customer participation
Service design
Service marketing research priorities
Service marketing

Grönroos, C. (2020), "Viewpoint: service marketing research priorities", Journal of Services Marketing , Vol. 34 No. 3, pp. 291-298. https://doi.org/10.1108/JSM-08-2019-0306

Emerald Publishing Limited

Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial & non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode

The purpose of this paper is to discuss two neglected but central topics within the domain of service marketing that, in my view, need urgent attention in service research. Because these topics are of such fundamental importance to the understanding of service marketing, I consider them just as important, if not more important, as any of the significant service research priorities that have been suggested in the literature. These topics are service and marketing . First, I discuss the research into these topics that exist, and then I suggest directions that, in my view, would enable further fruitful research into these topics.

State of current knowledge

Service innovation and design, transformative service research, service branding, accountability, service logic, digitalization and other topics have been suggested as important research priorities ( Ostrom et al. , 2015 ). These are, of course, central research topics in the field of service marketing today. However, there are two more fundamental aspects of service marketing that have been neglected in service marketing research and where solid service-focused models are missing, namely, service and marketing.

Rathmell (1974 , p. 7) made the following comment about service marketing research: “definitions, classifications, data, and concepts are lacking, noncomparable, or unreal from a marketing perspective.” He continued,

[…] moreover as one attempts to integrate marketing terms, concepts, and practices with firms, institutions and professions having their own traditions, customs, and practices which are quite foreign to conventional marketing (and much older), the linkage appears awkward and even improper (p. 7).

He also observed that service firms do not have one contact point with their customers covered by conventional marketing, but two – namely, marketing and production. The interactions between buyers/consumers and sellers/service providers that take place in the latter contact point are relevant to marketing in service firms (p. 6). Three years after Rathmell, Shostack (1977 , p. 73) observed that:

[…] merely adopting product marketing’s labels does not resolve the question of whether product marketing can be overlaid on service businesses. Can corporate banking really be marketed according to the same basic blueprint that made Tide a success?

Her conclusion was that “new concepts are necessary if service marketing is to succeed” (p. 73). My question is, how far has research into service marketing reached since these early days of modern service research? The sad answer is that it has not reached very far.

In a conference paper presented at one of the American Marketing Association’s service marketing conferences in the 1980s, I made the rather obvious remark about the development of service as an offering that “one of the most essential cornerstones in developing something is a thorough understanding of the phenomenon to be developed” ( Grönroos, 1987 , p. 81). In an article published six years later together with Hans Åke Sand, Chief Executive Officer of an innovative and successful car rental enterprise, we noted that “there is no generally accepted conceptual model […] of services as products, i.e. as objects to be developed, produced and marketed” ( Grönroos and Sand, 1993 , p. 45). Again, my question is, how far has research into service as an object of marketing or as an offering reached since those early days of service research? Again, the answer is equally saddening. During the past 15 years, service as a phenomenon has been discussed as part of the research into service as logic ( Vargo and Lusch, 2004 ; Grönroos, 2011 ). Recently, I have defined service as a phenomenon as providing help to another person’s or organization’s relevant processes in a way valuable to this person or organization ( Grönroos, 2019 ). However, since the 1980s and 1990s, very little has been published on service as an offering – that is, as an object to be innovated, developed, designed, produced, delivered and marketed. Studies on innovation, design and development of services are abundant, but the object of such research is seldom discussed and specified explicitly.

As marketing has been a driving force of modern service research and its dominating subareas, the conceptual development of service marketing should be a central research priority. As marketing of services cannot be understood conceptually without an understanding of what service as an object of marketing consists of, conceptual development of service as an offering or an object to be marketed should be another self-evident research priority in service research. Service and marketing are so central to service research that I will focus on them in the present article. First, marketing will be discussed and then service.

There were attempts to develop service marketing models, but what happened?

In the early days of modern service research, several conceptual models of service marketing were developed. In the 1970s and early 1980s, four models, in particular, were published: Eiglier and Langeard’s servuction model ( Eiglier and Langeard, 1975 ; Langeard and Eiglier, 1987 ), Shostack’s molecular model ( Shostack, 1977 ), Grönroos’s interactive marketing model ( Grönroos, 1978 ; Grönroos, 1982 ) and Booms and Bitner’s 7P model ( Booms and Bitner, 1982 ). In addition, Berry (1983) introduced the idea of relationship marketing , emphasizing the long-term timeframe of service marketing. Following the classification provided in Berry and Parasuraman’s (1993) analysis of the service marketing field, the servuction model represents the French school, the interactive marketing the Nordic school, and the 7P model the American school. of service marketing. The molecular model includes elements of both the first and second schools. These models are genuinely geared toward characteristics of service firms, predominantly the process nature of services and the impact of interactions between providers and customers, but they are based on somewhat different approaches. The servuction model is based on resources active in the service (production) process; the interactive marketing model is geared toward Rathmell’s observation that both conventional marketing and production processes influence customers and thus have marketing implications and take, at least partly, a process approach to marketing. The 7P model takes conventional marketing’s four decision-making areas as the starting point and adds three more Ps representing decision-making areas relevant to service firms. Basically, this model is a decision category model, but it includes process as one of the new service-specific decision-making categories. The molecular model emphasizes that to market services successfully, a number of other resources and processes influencing customers have to be taken into account in addition to conventional marketing activities. In various ways, all these models go beyond conventional models by including aspects related to service production and interactions between customers and service providers. As shown in Berry and Parasuraman (1993) , there were a large number of publications on service marketing in the 1980s and 1990s ( Zeithaml et al. , 1985 ; to mention but one), but the field was really not developed further. Then service research turned to other topics.

Enter service quality, exit service marketing

Following my, and to a larger extent Berry, Parasuraman and Zeithaml’s articles on service quality in the 1980s ( Grönroos, 1982 , 1984 ; Parasuraman, Zeithaml and Berry, 1985 ; Zeithaml et al. , 1988 ), an interest in service quality grew almost exponentially among service researchers. At the same time as this explosion of service quality studies took place in the late 1980s and 1990s ( Cronin and Taylor, 1994 ; Boulding et al. , 1993 ; Teas, 1993 ; Brady and Cronin, 2001 ), studies of service marketing more or less died out. Why did this happen? In my view, service marketing requires genuinely new approaches, which did not fit the conventional and dominating marketing mix management paradigm and kept researchers from continuing the studies of marketing in service firms. The conventional paradigm offered a too-heavy straitjacket to allow for boundary-spanning research approaches. However, service quality enabled researchers to still study how service firms could approach their customers to make them satisfied – a theme central to marketing – without having to place it in the marketing domain and challenge established marketing “truths.” Studies of service quality became a surrogate for studying marketing. Without putting it into a marketing framework and without having to move marketing as marketing into inconvenient directions geared to the characteristics of service, the production and interaction-related aspects could still be studied, but in a service quality domain. Whether this happened consciously or unconsciously can be debated.

As far as my early publications ( Grönroos, 1982 , 1984 ) labeled “service quality” were concerned, the goal was never to initiate research into the quality of services. Everything was a mistake ( Grönroos, 2001 ). In reality, I was interested in how customers perceive service as an offering or object of consumption. I was looking at the features of service offerings that customers perceived and appreciated as a starting point for further research on how to conceptualize service as an object of production, delivery and marketing. I just happened to choose the label “perceived service quality” for such perceptions. In hindsight, I should have called it “perceived service features” instead. Once the fast-spreading interest in service quality research occurred (and I was, of course, not its only initiator), it was too late to stop it. And service quality research did offer new insights into quality; for example, the observation that quality is not what firms produce and offer, but what customers perceive.

In conclusion, instead of exploring the nature of marketing in service firms and developing models of service marketing further, the service research community devoted itself to studying other service-related topics. Service quality was especially the topic of interest, as I understand it, as a surrogate for studying marketing issues directly, where researchers did not have to challenge the steadfast grip of the conventional marketing mix management view. As I said before, perceived service quality relates directly to the aspects of the servuction, molecular, interactive marketing and 7P models unique to service.

When the interest in service quality faded away toward the end of the 1990s, with the new focus on service as a perspective or logic on business and marketing, value and how value is created and co-created became key topics in service research ( Vargo and Lusch, 2004 ; Grönroos, 2011 ). However, the same thing as with service quality happened. This field of research exploded and, although it has been claimed that it is about a new logic for marketing, attempts to conceptualize marketing are largely lacking. At the same time, other topics of importance, such as design, innovation, customer experience, customer engagement, transformative service, service branding and digitalization have also drawn the attention of the research community. In none of these areas has conceptualizing marketing been of central interest.

How serious is this?

An absolute key research priority in service research is to finally continue the research into service marketing that took place in the early days of modern research into the service field. Unless a valid and acceptable model (or models) of marketing relevant to service is developed and found useful, none of the advances made in designing, innovating and digitalizing services, to mention just a few topics, can be fully used, or used at all. Marketing has to reinvent itself. Its credibility and use in firms has been in decline for a long time. In a section of a 2005 issue of the Journal of Marketing labeled “Marketing Renaissance,” supposedly devoted to reinventing marketing, Stephen Brown reported a study among top executives of major service-oriented firms associated with the Center for Services Leadership at Arizona State University. He wrote, “notably, none of the executives mentioned marketing as being responsible for the customer.” The executives indicated that “marketing and sales often have a major role in making promises to customers and in generating new business. However, the keeping of promises and building customer loyalty is typically considered the responsibility of others in the enterprise ” ( Brown, 2005 , p. 3, italics added). In the same section, these observations are reinforced by Sheth and Sisodia (2005 , p. 11), who note that “many strategically important aspects of marketing […] are being taken away by other functions in the organization.” The only other important observations for reinventing marketing from the 12 papers in this marketing renaissance section, in my view, are the general conclusion that there is “[a] weak linkage between marketing scholarship and marketing practice” ( Brown, 2005 , p. 3), and Sheth and Sisodia’s(2005 , p. 12) concluding remark:

Can marketing’s reputation be redeemed? Not unless it resolves the fundamental contradiction at its core: Marketing claims to be about representing the customer to the company, but it remains mostly about representing the company to the customer, using every trick in its bag to make customers behave in the company’s best interests.

Since then, the development of digitalization has strengthened the position of the customers, but the conventional marketing models have had difficulties handling this.

The observations presented above should be taken seriously. Marketers do not honestly have customers’ best interests in mind, in parallel with the firm’s interest. Moreover, employees other than the marketers are responsible for keeping customers and, therefore, for making customers feel satisfied with how the firm serves them and also for their continued patronage to the firm. For the research community, it should be a wake-up call drawing researchers’ interest to study how marketing can be reinvented to fit today’s customer communities and business practices. So far, neither service researchers nor marketing scholars, in general, have reacted. As a consequence, marketing continuously becomes less relevant to firms and top management, and only tactical, if anything, and marketing as an academic discipline loses credibility as part of the management and business administration field.

Reinventing marketing through promise theory

Keeping Sheth and Sisodia’s criticism of contemporary marketing as not representing the customers to the firm in mind, the ultimate goal of marketing should be to make the firm relevant to its customers ( Grönroos, 2015 ; italics added). Conceptualizing marketing should be founded on this requirement. Furthermore, marketing is a process that includes many elements, such as creating interest in the firm and its offerings, making customers who have bought the offerings feel satisfied with them and creating enduring relationships with customers. In a service context, the offering, the service that is consumed, is a process and to a varying degree, it emerges in interactions between the service provider and the customer. Moreover, as emphasized by customer-dominant logic, the customer puts offerings into their customer ecosystems and, based on that, they determine the importance and value to them of such offerings ( Heinonen and Strandvik, 2015 ). All this needs to be incorporated in attempts to conceptualize service marketing.

For me, promise theory , already introduced in marketing in the 1980s by Calonius (1986) , offers solid ground to build upon. It pinpoints and elaborates on the very problem of marketing demonstrated in Stephen Brown’s contribution to the marketing renaissance discussion, namely, that marketing has reverted to promise-making and lost control of actions and processes that secure customer satisfaction and loyalty. As Bitner (1995 , p. 246), inspired by Calonius, proposed in the title of a promise-related article, “it is all about promises.” As Calonius formulated promise theory as a foundation of market behavior:

[a] promise is a more or less explicitly expressed conditional declaration of assurance made to another party, or to oneself, with respect to the future, stating that one will do […] some specific act. […] The action or intentional activity called forth by a promise […] will occur with some probability in the near or more distant future ( Calonius, 2006 , p. 422).

This simply means that marketers should make promises to their customers that can be kept and then keep these promises, thereby fulfilling the expectations among customers created by the promises made. If such promises relate well to the customers’ life situations, activities and needs – in other words, to their customer ecosystems – this behavior should make the firm relevant to them and marketing should achieve its ultimate goal.

Developing marketing models based on promise theory requires that marketing is conceptualized as a promise management process, where making and keeping promises are integrated. Instead of being a rather static marketing conceptualization based on decision categories, such as the 4P model, this would be a dynamic marketing-as-a-process conceptualization. However, the promise-making/promise-keeping dichotomy is not new to marketing. The 4P model includes the product variable, which is clearly thought to fulfill the promise-keeping requirement. The problem is that the promise-keeping capacity of the product variable is only inherent in the model, and not explicitly emphasized or even pointed out. Furthermore, as the product is frequently given to the marketers, the promotion, price and place variables of the model take over, and they are all geared toward promise-making. As a conclusion, marketing mentally and factually becomes a promise-making issue, where the product is thought to keep promises made more or less automatically.

In a service context, this does not function, because in service there are no products as pre-produced, tangible artifacts. Service is a process-based business ( Edvardsson et al. , 2005 ), where promises are made of processes taking place in the future and promises are kept through how well such processes function to a smaller or larger extent in interactions with the customers. This changes things immensely. Promise-keeping cannot be taken for granted anymore. For the firm’s marketing, keeping a promise does not happen automatically, as conventional models of marketing assume. The process that the customers experience must be managed in a customer-focused manner – that is, in a way that has the marketing effect of making the customers satisfied and willing to engage with the firm in the future as well. Moreover, what is “the firm’s marketing?” We are used to thinking of marketing as a separate function alongside other business functions, often managed by a marketing department of full-time marketers. As the process of keeping promises is outside the immediate responsibility and control of those in the firm who make promises about this process – that is, the full-time marketers – marketing as promise-keeping extends marketing beyond those who, according to conventional marketing models, are considered the marketers .

Conceptualizing service marketing as promise management

Marketing as promise management means that three separate processes need to be studied and developed, namely, a process of promise-making, a process of promise-keeping, and, in addition, a process of promise-enabling. In conventional marketing, relying on a marketing department of full-time marketers, those responsible for marketing activities are thought to be marketing professionals. However, the service or frontline employees interacting with customers in the service (production) process are employed in other non-marketing business functions. Primarily their job is to make sure that the process functions well from a technical point of view. However, as part-time marketers , to use a term introduced by Gummesson (1991) , they fulfill a key marketing function when interacting with customers. As Gummesson (1995) also notes, there normally are many more part-time marketers than full-time marketers, and they meet customers at the very point of service production and consumption. In creating customer satisfaction and loyalty, and in generating resales, their role is critical. To make sure that the part-time marketers are prepared and willing to fulfill their role in the promise-keeping part of the total marketing process, activities and processes labeled internal marketing ( Grönroos, 2015 ) in the service literature are needed. Through internal marketing, it is assured that promises can be made and kept successfully, such that customers buy and become satisfied with what they have bought. This is promise-enabling.

In an article published in 2006, I draw guidelines for the development of marketing and suggest an overarching marketing definition based on the promise management approach:

Marketing is a customer focus that permeates organizational functions and processes and is geared towards making promises through value proposition, enabling the fulfilment of individual expectations created by such promises, and fulfilling such expectations through support to customers’ value-generating processes, thereby supporting value creation in the firm’s as well as its customers’ and other stakeholders’ processes ( Grönroos, 2006 , p. 407).

These guidelines point out that, when conceptualizing service marketing, one needs to distinguish between those resources and activities that take responsibility for making promises and those that take responsibility for keeping promises. The former resources are probably mainly full-time marketers, whereas the latter are part-time marketers as well as other resources and systems – physical and digital – that the customers interact with or are exposed to in some other way. The servuction, molecular, interactive marketing and 7P models of the early days of service research include such resources as well as processes active in such interactions in various ways. In addition, the role of the customers themselves as a resource in service marketing is emphasized in some of these models and in early service research. Furthermore, the promise management definition emphasizes that promises made create individual expectations among customers and that those responsible for marketing in the promise-keeping phase must be prepared to take this into account when interacting with customers. This is part of internal marketing as the promise-enabling process.

The promise management guideline and overarching definition offer many opportunities for service researchers to conceptualize service marketing and develop more detailed models of service marketing and, for example, of the various sub-processes of promise management.

What is “the firm’s marketing”?

Earlier, I raised the question of what is meant by “the firm’s marketing.” What is included in the marketing process of a firm? Conventional marketing thought assumes that marketing is a separate function frequently managed by a marketing department. In the literature, “marketing department” is often used as a synonym of “marketing function.” However, when the product is replaced by the service process, and frontline service employees, who are part of other functions in the firm, take on the role of part-time marketers, marketing cannot be viewed in the traditional, rather simplistic manner anymore. As Wilkie (2005 , p. 9) concluded his analysis in the discussion of the renaissance of marketing, “in brief, we need a larger conception of marketing.” Furthermore, marketing cannot be organized in traditional ways. As the promise management guideline and definition imply, because frontline employees/part-time marketers belong to several functions, marketing permeates several organizational functions. An obvious conclusion is that marketing can only be partly organized ( Grönroos, 2015 ). The promise-making process can in most cases be organized in a separate department, but the promise-keeping process is spread throughout the organization. Therefore, it cannot be organized in any conventional structures. Instead, in the context of promise-keeping, marketing must be instilled as a customer-focused mindset ( Grönroos, 2015 ). Instilling this mindset demands internal marketing efforts. How to ensure that marketing functions well in the promise-keeping sub-process without organizing it offers an abundance of important and interesting research opportunities. However, this requires that researchers move out of their comfort zone of studying marketing issues through traditional lenses. As Webster (2005 , p. 6) formulates it, to develop marketing “we must tolerate work that bursts through and redefines the currently accepted boundaries of our intellectual domain.”

What about the term “marketing”?

When developing service marketing, a word about the term “marketing” is warranted. When people outside of marketing’s traditional boundaries become part of marketing, and when business functions other than marketing become part of the firm’s total marketing process, it becomes doubtful whether “marketing” signifies the phenomenon we are talking about very accurately. It is a matter of something much larger than getting out into the market. Employees who have different background and training easily find marketing inherently unacceptable and resist being part of it. In 1999, I suggested that dropping the term may serve the introduction of marketing into service firms better than using it ( Grönroos, 1999 ). It is also a matter of marketing’s credibility among employees, customers and top management. Twenty years later, this suggestion still seems to be too controversial to be picked up in any serious research into marketing. However, in the discussion of a renaissance for marketing, Sheth and Sisodia (2005 , p. 12) make the point that “the word ‘marketing’ has lost so much credibility that companies would be better off using the designation of chief customer officer rather than CMO.” Clearly, they too find the term “marketing” problematic.

In conclusion, key research priorities for future service research that relate to the marketing domain include the nature, scope, boundaries and content of service marketing, how to organize for service marketing and even whether “marketing” is a term that enables the successful introduction of service marketing in firms or whether a different term is needed.

What should be marketed is also missing in service research: the service offering

Product is a key marketing variable in the conventional 4P model. Without an understanding of the product to be marketed, successful product marketing outcomes cannot be expected. This is, of course, also true for service marketing. How can the object to be marketed be understood and conceptualized in the context of services? This is critical for other research areas besides marketing within the service domain as well. For example, innovation, design, branding and transformative service have drawn extensive attention from service researchers. The Journal of Service Research has published special issues on service design (February 2008) and transformative service research (August 2015). The articles published in these issues develop new thoughts, concepts and models largely based on an understanding of customers and their processes, which, of course, is important. However, what also is important is an explicit understanding of what constitutes the service that is innovated, designed and branded, and which the customers purchase and consume. Models or conceptualizations or even discussions of this are lacking. In an overview article of service innovation, Helkkula et al. (2018) define four archetypes of innovation in the extant research, namely, output-based, process-based, experiential and systemic archetypes. Here, too, service as an object of innovation is not explicitly present.

Given the amount of research on the many subfields of service that has been published, it is, in my view, worrying that there is no clear model or models of service as an object or offering to be produced, marketed and consumed. This object is a process ( Edvardsson et al. , 2005 ), and as a phenomenon, it is something that aims to help, for example, customers to achieve goals that are valuable to them ( Grönroos, 2019 ). However, what features or elements constitute this object? In the following paragraphs, I use the term “service offering” for such an object.

In the 1970s and 1980s, some publications on service included observations about service offerings. It was noted that they included two types of services – namely, core and auxiliary services ( Normann, 1984 ) – as part of a service package ( Sasser et al. , 1978 ; Normann, 1984 ). In the context of their servuction model, Langeard and Eiglier (1987) discuss an offering system. In the context of service development, Edvardsson (1996) made the point that customers have what he termed primary needs, which are fulfilled by a set of core and auxiliary service elements – such as guest rooms, booking, check-in service, and breakfast service in a hotel context – and secondary needs, which relate to how these services function as processes. The words “primary” and “secondary” are not used to indicate any difference in nature or importance; he emphasized that both types of customer needs have to be acknowledged.

Edvardsson’s model was partly based on a conference paper from 1987 ( Grönroos, 1987 ), where I pointed out the need to distinguish between two layers in a service offering, namely, a basic package of service elements and an augmentation of this package. This augmentation makes the service process part of the service offering. In this model, the augmentation includes three variables: accessibility of the service; interactions between the customer and the many service provider resources; and finally the customer’s ability to participate in the service process, termed customer participation ( Grönroos , 1987, 2015 ). Later, in the context of digital services, together with Kristina Heinonen and other colleagues ( Grönroos et al. , 2000 ), we suggested that the accessibility and interaction variables merge into one information variable. In the same conference paper, I also emphasized that auxiliary services added to a core service (lodging, in the hotel example) in a service package are of a different nature and fulfill different purposes. For example, booking and check-in services in the hotel example are mandatory services. If they are missing or not accessible, the customer cannot use the core service. However, breakfast service is not mandatory in the same sense. The purpose of such a service is to enhance the service offering, whereas the purpose of the former types of services is to enable the use of the core service. Hence, for the understanding of the service package, it is important to distinguish between the core service, offering-enabling services and offering-enhancing services ( Grönroos, 1987 ; terminology as in Grönroos, 2015 ).

Conceptualizing service as an object or offering

When developing a model of service offering – that is, of services as objects for production, marketing and consumption – a critical starting point is that services are not product-like objects but processes that lead to an outcome. As demonstrated by the perceived service quality model ( Grönroos, 1984 ), both the outcome and the process influence the customers’ perceptions. Furthermore, the distinction between customers’ primary needs and secondary needs, as suggested by Edvardsson (1996) , should be taken into account. To fulfill primary needs, the service model must include service elements, such as guest rooms and booking, check-in and breakfast services in the hotel example used earlier. To fulfill secondary needs, the service model must also include process-related aspects of the service, which guarantee that the service elements function in a customer-focused manner. The service elements form the service package, but this package is not the service as an object or offering. They only make sure that the service’s intended outcome is achieved. In perceived service quality terms ( Grönroos, 1984 ), they ensure that the technical outcome quality can be delivered. The role of the process-related aspects is to guarantee that the service elements of the service package also function in a desired manner, such that a satisfying service emerges. In perceived service quality terms, they ensure that the functional process quality requirement is achieved. When conceptualizing services, however it is done, both service package elements and service process-related aspects must be included.

When developing the elements of the service package, it is also essential to observe that they may fulfill different purposes, such as mandatory elements enabling the use of the core service and optional elements enhancing the perception of the service. Most service elements can be both enabling and enhancing. To use a car rental example ( Grönroos and Sand, 1993 ), the core service is transportation by a rented vehicle. Access to a wanted vehicle is a purely enabling service element, whereas, for example, the reservation system, information about terms and conditions, vehicle return system and payment system can be both enabling and enhancing service elements. Complaints handling and service recovery are examples of purely enhancing service elements.

In my 1987 model, I proposed that accessibility, interaction and customer participation variables are used to augment the service package and cover the process-related aspect of services ( Grönroos, 1987 ); and in 2000 study, my colleagues and I suggested that information and customer participation variables can be used to conceptualize the augmentation of digital services ( Grönroos et al. , 2000 ). These are only research-based examples from the literature of ways of conceptualizing the service package and of augmenting the elements of this package. This “augmented service offering” approach offers an abundance of opportunities to further conceptualize service as an offering or object. However, regardless of how models of services as objects or offerings are conceptualized, both service elements and the process-related augmentation of such elements need to be taken into account. Otherwise, the model will not be conceptualized in a way that meets the customers’ view of what constitutes services.

Concluding remarks

In the present article, I have made the point that marketing and service as objects of marketing or offerings are neglected research topics within the domain of service marketing and that these topics should be highly prioritized in service research. This does not mean that other suggested research priorities are less important – on the contrary. However, the need to study service and marketing again has not been voiced for decades. Therefore, it is essential to draw the service research community’s attention to these topics very fundamental to our field and to emphasize the urgent need to study them. Moreover, service and marketing form the very foundation of our domain, and without proper understanding of them, the development of other current and future service topics may generate less valid results.

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Corresponding author

About the author.

Christian Grönroos is a Professor Emeritus of Service and Relationship Marketing at Hanken School of Economics, Finland. He is a pioneer developing the academic field of service marketing and Co-founder of the Nordic School of Service Marketing Research. He has published extensively on service marketing and service management topics. His most recent activity is a set of short video lectures on “Principles of Service Management” on YouTube. In 2013 he was selected Legend in Marketing by the Sheth Foundation.

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Int J Environ Res Public Health

Quality in Customer Service and Its Relationship with Satisfaction: An Innovation and Competitiveness Tool in Sport and Health Centers

José Álvarez-garcía.

1 Financial Economy and Accounting Department, Faculty of Business, Finance and Tourism, University of Extremadura, 10071 Cáceres, Spain; se.xenu@zeravlaepep

Encarnación González-Vázquez

2 Business Management and Marketing Department, Faculty of Economics and Business, University of Vigo, 36310 Vigo, Spain; se.ogivu@zelzge

María de la Cruz Del Río-Rama

3 Business Management and Marketing Department, Faculty of Business Sciences and Tourism, University of Vigo, 32004 Ourense, Spain

Amador Durán-Sánchez

4 Economy Department, Faculty of Economics and Business, University of Extremadura, 06071 Badajoz, Spain; se.xenu@nasnarudma

The objective of this research was to analyze the influence of the dimensions that enable the rating of service quality perceived by users of sport and health centers in the satisfaction they experience from the service received. In order to present the working hypothesis, a bibliographic review on the concept and dimensions of perceived service quality was carried out, as well as its relationship with satisfaction. The rating scale sports organizations (EPOD) was used as a measurement instrument. The application of a regression analysis was used to test the hypotheses. As a prior step, the measurement scales were validated and an exploratory factor analysis was applied to determine the structure of the variables considered. The regression models proposed show the joint influence of the dimensions used by the users to rate perceived service quality in their satisfaction. The results enabled us to observe that the dimensions considered in the model explained 75.7% of satisfaction, with the facilities and material, together with communication and activities, having the most significant influence on satisfaction. Meanwhile, dimensions that had less impact were the monitor and the staff. It is clear that there is a strong correlation between perceived quality and satisfaction with service.

1. Introduction

Currently, research shows that success and competitiveness in the management of sport and health centers requires more efficient management. In this sense, quality management, as one of the 25 most-used management tools [ 1 ], is essential [ 2 ]. Quality management is understood from two perspectives: The internal perspective (objective quality), focused on the standards of the service, and the external perspective (subjective quality), focused on quality as satisfaction of users’ expectations. The latter is currently the most-followed perspective in the service sector [ 3 ].

Thus, innovation and quality are the two key factors for business success [ 4 , 5 , 6 , 7 , 8 , 9 ]. Both concepts are linked in the sense that innovation is a part of continuous improvement [ 10 ] which, in turn, forms a fundamental part of quality. Porter [ 11 ] stated that the competitiveness of a country and, therefore, of its industrial and economic fabric, depends on the capacity to innovate and improve. With respect to organizations, innovation allows for economic sustainability and for their growth by generating competitive advantages [ 12 , 13 , 14 , 15 , 16 ].

Innovation is not exclusively associated with creativity and the generation of new products and services, but also refers to new forms of management and processes [ 17 , 18 ]. One of the most widely used definitions of innovation is provided by the Oslo Manual [ 19 ], which defines it as “the introduction of a new or significantly improved product (good or service), of a process, of a new organizational or marketing method, in the internal practices of the company, the organization of the workplace or external relationships”. Therefore, several types of innovation are distinguished: Product, process, organizational, and marketing innovation.

In this sense, the implementation of quality management systems is part of organizational innovation [ 20 , 21 , 22 , 23 , 24 ], since it involves the implementation of new organizational methods in the business. Therefore, the quality and, consequently, the implementation of quality management systems and the processes that are derived from it, become a tool for innovation and competitiveness in sport and health centers.

In the context of sports organizations, reference is made to service quality as “a differentiation strategy to increase productivity and profitability, as well as to improve the company’s image and achieve user loyalty” [ 25 ] (p. 250). In addition, service quality also enables knowledge of users’ perception of the quality of the service received, which is necessary to improve user satisfaction, as well as improve the competitiveness and viability of organizations. It should not be forgotten that satisfaction in the academic literature is considered a precedent for trust, mouth-to-ear communication [ 26 ], complaints [ 27 ], and loyalty [ 28 ].

In this research, carried out in the context of sport and health centers, the external perspective of quality is considered in which the client becomes the central axis of sports organizations. Therefore, it focuses on the concept of “perceived quality” of services, which is the way to conceptualize the predominant quality in the field of services.

In this sense, it must be taken into account that “a service is of quality to the extent that it meets or exceeds clients’ expectations” [ 29 , 30 , 31 ] and the concept is operationalized in practice by users comparing their expectations of the service with the perception that is formed once it is received [ 32 ]. In this way, quality ceases to be something objective (it focuses on the producer’s perspective) and instead becomes subjective, focusing on what the consumer says it is [ 29 ], as “only consumers judge quality: all other judgments are essentially irrelevant” [ 31 ] (p.18).

Research carried out on quality in sports services and consumer satisfaction has become important in recent years. According to Calabuig [ 33 ], it is mainly developed from three points of view in the sports sector: Psychosocial, the economic-business perspective, and the marketing perspective, focused on the consumer (studies based on SERVQUAL and alternative studies). This research follows the marketing perspective, whose research focuses, according to Pérez [ 34 ] (p.128), on “how to improve quality perception and the sense of satisfaction”.

Although several studies have been carried out following this perspective [ 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 ], authors such as Tsitskari et al. [ 49 ] and Arías-Ramos et al. [ 50 ] (p.106) state that these types of studies are not sufficient; “there are many issues to be addressed, lines of research to be continued and uncertainties to be resolved on the assessment of perceived quality and user satisfaction in sports organizations”.

In this context, this research is aimed at analyzing the influence of the dimensions that enable the rating of the quality of service perceived by users in the satisfaction they experience with it, which enables to us observe whether the perceived quality of a sports service is directly related to the satisfaction level. The empirical study was carried out in a sport and health center with a sample of 206 clients. The measurement instrument known as the rating scale sports organizations (EPOD) was used.

This article is structured as follows. After the introduction, where the subject matter of the study is contextualized, the study is justified and the objective is presented. Section 2 contains the theoretical reference framework (concept of perceived quality of the service and its relationship with satisfaction) and the work hypotheses are presented. The methodology used (target population, measurement questionnaire, and data analysis) is described below. The results are collected in Section 4 , and finally, the conclusions obtained are discussed and presented.

2. Review of the Literature

2.1. perceived service quality concept.

The starting point to define the concept of “perceived service quality” is defining the terms “service” and “service quality”. In this sense, the definition of service provided by Grönroos [ 30 ] is one of the first definitions and delimits service as that activity or series of activities of a more or less intangible nature that normally, but not necessarily, take place through interactions between the client and the employees of the service company who try to solve the consumer’s problems.

This definition, together with the one provided from a different approach by Lovelok, approach the perceived service quality concept by taking into account the satisfaction of expectations. Lovelok [ 51 ] (p.491) understands customer service as activities aimed at a task that includes interactions between clients and the organization and seeks the mutual satisfaction of the expectations of both, so it must be designed with two objectives in mind: Customer satisfaction and operational efficiency.

With regard to the service quality term, its definition is very complex since the intrinsic characteristics of the services means, on the one hand, that the quality practices applied must be different from those for tangible products [ 49 , 52 ] and, on the other hand, a greater difficulty is involved when evaluating the quality of a service. In this sense, Parasuraman et al. [ 32 ] (p.36) states that “the difference between the evaluation of the quality of a service and that of a good by a consumer is not in the process, but in the nature of the characteristics on which the evaluation is performed”.

These characteristics were specified by Parasuraman et al. [ 32 ]: Intangibility, inseparability of production and consumption, or simultaneity, heterogeneity, or variability, expiration. In Parasuraman et al. [ 32 ] and Grönroos [ 53 ], a broad discussion of the differences between services and physical goods can be seen. According to Zeithaml [ 54 ] and Stanton et al. [ 55 ], the intangible aspects are difficult to identify and quantify and make it difficult to establish precise specifications to standardize their quality. On the other hand, they are susceptible to different evaluations by clients, which makes the measurement and evaluation of quality difficult [ 55 ]. The inseparability in the services of production and consumption, as well as the perishable nature and the potential heterogeneity or variability in the performance, make the precision of quality difficult [ 32 ] (p.35).

In this context, as already mentioned, there are many definitions in this regard [ 54 , 56 , 57 , 58 ] and their review provides two different views or approaches when defining the service quality term: Objective and subjective quality [ 53 ] (p.38). On the one hand, the objective quality or internal vision of quality focuses on the technical aspects [ 59 ] from the producer’s perspective, as well as the subjective quality or external vision of quality in which clients’ requirements are emphasized, thus emerging the “perceived quality” concept. This last concept was introduced by Gönroos [ 58 ] when considering the idea that clients compare their expectations with the service received, with the result of this process being the perceived quality of the service. This concept was developed later, both methodologically and empirically, by Parasuraman et al. [ 32 , 60 ]. An important aspect to mention is that these two visions gave rise to two schools of thought: The Nordic School and the North American School.

In the case of the Nordic School, its main representatives Grönroos [ 61 , 62 , 63 ], Gummesson [ 64 ], and Lehtinen and Lehtinen [ 65 ], focus on the concept of service quality from the point of view of the product, with efficiency being the basic objective for which standards are used for its control [ 65 ]. The Grönroos Service Quality Model [ 58 ] established two dimensions for service quality which interact between each other: Technical quality or design of the service, referred to as “what” service the client receives (result), being susceptible to be measured by the company and evaluated by the consumer; and the functional quality or performance of the service, which deals with “how” customer service (process) is provided. Both dimensions are compared with previous expectations by the client, which are influenced by the result of the service, by the way it is received, and by the corporate image [ 58 ]. Subsequently, this conceptual model of Grönroos, in which perceived quality is defined as a result of the comparison between the expected and received service, was moved to the United States and developed by Parasuraman, giving rise to the emergence of the North American School.

Bearing in mind that this last perspective is the one that best fits sports services, which is the scope of study in this research, it is the one that was developed in more detail. Thus, Parasuraman et al. [ 66 ] (p.3) defined perceived service quality by the client, as an overall assessment of the consumer regarding the superiority of the service resulting from the comparison made by clients between the expectations and perceptions regarding the performance of the service received. This definition of perceived quality became the most widely used way to conceptualize quality from the perspective of services and is the basis of the theoretical and methodological approach of Parasuraman et al. [ 32 ], in which the quality process in services is explained.

These authors posed the question of “What is service quality?” in their initial investigation. Thus, the concept of perceived quality [ 32 ] arised. They also determined the dimensions used by clients to rate services [ 66 ]. Finally, they developed a conceptual and empirical model to measure service quality: The SERVQUAL model, represented graphically by Zeithaml et al. [ 67 ] (p.26), and defined as “a summarized multiple-scale tool with a high level of reliability and validity that companies can use to better understand the expectations and perceptions that customers have regarding the service received”.

As shown, the two factors that determine perceived service quality are expectations and perceptions [ 66 ]. Expectations are defined by Parasuraman et al. [ 66 ] (p.17) as clients’ desires or needs and they are determined, as reflected in the conceptual model, by previous experiences, clients’ current needs and demands, the company’s external or formal communications, mouth-ear communication between clients, and the corporate image. Perceptions are defined as consumers’ beliefs regarding the service received, which will be determined by the dimensions which clients consider in order to rate the service.

In this regard, in the literature on the subject, there are divergences regarding these dimensions and there is no consensus. Garvin [ 68 ] consider eight dimensions (performance, characteristics, reliability, attachment, durability, service aspects, aesthetics, perceived quality), Lehtinen and Lehtinen [ 65 ] consider three dimensions (physical, corporate, and interactive quality), and Grönroos [ 58 ] takes into account the technical or result dimension, the functional or process dimension, and the corporate image.

However, the most-considered multidimensionality of service quality by researchers in this field is the one proposed by Parasuraman et al. [ 32 ], who consider that perceived quality is made up of 10 dimensions: Tangible elements, “appearance of physical facilities, equipment, staff and communication materials”; reliability, “ability to implement the service promised reliably and carefully”; responsiveness, “willingness to help customers and provide them with a quick service”; professionalism, “having the required skills and knowledge of the process of providing the service”; courtesy, “attention, consideration, respect and helpfulness of the contact staff”; security, “no dangers, risks or doubts”; credibility, “veracity, belief, honesty in the service provided”; accessibility, “accessible and easy to contact”; communication, “keeping clients informed using a language they can understand, as well as listening to them”; and understanding the client, “making the effort to know the clients and their needs” [ 67 ] (p.24). Subsequent research by these authors [ 66 ] reduced them to five dimensions: Tangible elements, reliability, responsiveness, security (including professionalism, courtesy, credibility, and security), and empathy (including accessibility, communication, and understanding of the user).

In summary, the concept of perceived service quality is a complex variable, with several definitions in this regard. This was observed by Díaz and Pons [ 69 ] (p.53), who, after analyzing the literature on perceived service quality, proposed two perspectives when defining the concept: From the perspective of customer perception [ 54 , 70 , 71 ] and from the perspective of customer expectations and perceptions [ 32 , 72 , 73 ]. However, in recent years, the most recurring perceived quality concept has been one which contextualizes quality in the field of services from the client’s perspective and is conceptualized by comparing the client’s expectations with the perceptions about the service received. According to Zeithaml et al. [ 31 ] (p.18), “only consumers judge quality: all other judgments are essentially irrelevant”.

The research conducted by Grönroos [ 58 ] and Parasuraman et al. [ 32 , 66 ], aimed at defining the concept of perceived quality, gave rise to two schools and their corresponding models of perceived service quality. As Gómez [ 74 ] (p.53) states, “to have a more complete vision and to finish understanding the concept of perceived service quality, it is necessary to know the different theoretical models based on this construct”. In the case of the North European or Nordic School, its integral models are the following: Models of quality of service or image [ 58 ], the Quality Model of Grönroos and Gummerson [ 53 ], augmented service offering [ 53 ], “Servuction” Model by Eiglier and Laneard [ 75 ], and the three-component model [ 76 ]. The North American School integrates six models: The SERVQUAL Model [ 32 ], Augmented Quality Service Model [ 77 ], SERVPERF Model [ 78 ], Multidimensional, Hierarchical Model [ 79 ], service quality model of Bolton and Drew [ 80 ], and Bitner service quality model [ 81 ].

2.2. Relationship between Service Quality and Consumer Satisfaction

In the previous section, the concept of perceived quality was broadly discussed, so the starting point of this section is to define the term “consumer satisfaction”. Two major lines of research in recent years, the cognitive model [ 82 ] and emotional model [ 83 ], have been integrated, leading us to consider satisfaction as a post-consumer response or assessment [ 84 ] susceptible to change in each transaction [ 85 ].

There is a great similarity between the concepts of perceived quality and satisfaction [ 86 ]. However, most researchers suggest that both concepts are different constructs and that service quality is a broader concept than satisfaction. Thus, Parasuraman et al. [ 66 ] refer to the differences between both concepts in relation to durability. Thus, perceived quality refers to an enduring attitude related to the superiority of a service, while satisfaction is a transitional assessment of a specific transaction in which a comparison is made with what was expected [ 85 ]. To Oliver [ 87 ], the differences are that when the consumer assesses the perceived quality, the predominant dimensions are those of a cognitive nature and, in the case of satisfaction, they are emotional in nature.

These differential characteristics, which are discussed in the literature, led Zeithaml et al. [ 86 ] to propose that the difference between both concepts is based on the fact that satisfaction involves an assessment made by the client for a specific transaction [ 88 ] and requires previous experience, since this assessment depends on the consumer’s previous expectations [ 76 , 89 ], whereas service quality can be perceived without the need for a direct experience with it [ 66 ].

There are many who affirm the existence of a relationship between both concepts [ 54 , 66 , 78 , 90 ]. However, they do not reach a consensus regarding the causal relationship between both concepts. Thus, Iacobucci et al. [ 91 ] state that there are two clearly differentiated positions: Those that support the idea that satisfaction is a consequence of perceived quality [ 66 , 78 , 92 , 93 , 94 , 95 ] and research that supports the inverse relationship, considering satisfaction as an antecedent of service quality [ 59 , 80 , 81 , 96 , 97 ]. However, there is also an intermediate position, in which satisfaction is considered both an antecedent and a consequence of the perceived quality of service. Representatives of this position are Parasuraman, Zeithaml and Berry [ 98 ], Rust and Oliver [ 76 ], and Martínez-Tur, Peiró and Ramos [ 85 ].

In this context, the following working hypotheses were proposed:

H1: The service quality dimensions have a positive influence on the satisfaction experienced by the users of sport and health centers.

H2: The service quality dimensions have a positive influence on the satisfaction with the facilities experienced by the users of sport and health centers.

H3: The service quality dimensions have a positive influence on the satisfaction with the organization of activities that the users of the sport and health centers experience.

H4: The service quality dimensions have a positive influence on the satisfaction with the activities experienced by the users of sport and health centers.

3. Methodology

3.1. universe, sample, and questionnaire.

The research was designed by organizing the collection of data in order to comply with the proposed objective through a structured questionnaire addressed to users of a sport and health center. To calculate the representativeness of the sample, only the subscribers were taken into account. Users who use the service occasionally, which represent a very small percentage, were excluded. Thus, the target population was made up of 1512 subscribers, and 206 users responded to the questionnaire (incomplete questionnaires were discarded), which represents a response rate of 13.62% and a margin of error of 6.35%, taking into account a 95% confidence level (Z = 1.96 p = q = 5).

The questionnaire was structured in three parts. First, to measure the perceived service quality, the rating scale sports organizations (EPOD) was created by Nuviala et al. [ 99 ], adapted to the sport and health centers where the study was carried out (29 items). This scale “is a tool for practical and direct application on the perception that users of sports services have of the sports organization and the services it provides” [ 99 ] (p.10). The original scale consists of 28 items grouped into four dimensions: Sports experts, facilities and material resources, activities, and image of the organization.

The second part of the questionnaire included the scale to measure user satisfaction with the service, which was divided into three dimensions: Satisfaction with the facilities (five items [ 100 ]) satisfaction with the organization (three items [ 99 ]), and satisfaction with the development of the activity (four items [ 101 ]). The last part of the questionnaire included the data that enabled us to define the sample profile. Five-point Likert measurement scales were used (1–totally disagree to 5–totally agree and 1–not at all satisfied to 5–very satisfied).

Regarding the profile of the user of the sport and health center, the user is between 18- and 40-years-old (77.6%), male (66.99%), student occupation (32.4%), or works in the private sector (31.07%), with a secondary education level (49.51%). This user usually attends the sport and health center three days a week (43.69%) on average, preferably in the afternoon (55.83%). The reasons for being a user of the center are: Proximity to home or work (20.55%), because of the treatment received (10.84%), and because of the range of activities desired (9.22%). The main reason for sports is entertainment in 40.29% of cases and for aesthetic reasons in 31.07% of cases.

3.2. Data Analysis Techniques

The statistical program SPSS 19.9 (IBM, Armonk, NY, USA) (Statistical Package for the Social Sciences) was used to perform the data analysis and was carried out in two phases. First, a descriptive study of the sample (mean and standard deviation) was carried out and the measurement scales were validated, taking into account the psychometric properties of reliability, validity, and unidimensionality [ 102 ]. To evaluate the reliability and delimit the number of items that measure each scale, Pearson’s item-total correlation coefficients were considered (they should not exceed 0.3 according to Nunnally [ 103 ]) and Cronbach’s α [ 104 ] was estimated (must be greater than 0.7).

The analysis of the unidimensionality enabled to us to find the structure of dimensions of the proposed scales. Prior to its performance, it was found that the data were adequate to perform the exploratory factor analyses: Analysis of the correlation matrix, Bartlett’s Sphericity test (χ 2 high and sig. > 0.05), the Kaiser-Meyer-Oklim (KMO) measure (>0.7, median: >0.8, good and 1> = KMO > 0.9, very good), and the sample adequacy measure were acceptable (unacceptable for values lower than 0.5, small values should be removed from the analysis). Unidimensionality was tested through the percentage of variance explained and the factor loadings of each indicator, for which an exploratory factor analysis of main components with varimax rotation was carried out [ 105 ].

Second, the multiple regression analysis was applied to contrast the hypotheses proposed. This process enabled us to study the relationship between a dependent variable (satisfaction) and its independent or predictive variables (dimensions of perceived service quality) through the estimation of the regression coefficients that determine the effect that the variations of the independent variables have on the behavior of the dependent variable. Prior to the regression analysis, the underlying assumptions on which this type of analysis is based were verified (linearity, independence, homoscedasticity, normality, and noncollaterality).

4.1. Validation of Measurement Scales

First, the internal consistency of the scale that measures the perceived quality of the service was analyzed through reliability analysis (item-total correlation and Cronbach’s α). Taking into account the item-total correlation, it was not necessary to eliminate any items, since all of them were above the recommended minimum of 0.3. Cronbach’s α that measures the reliability of each factor is higher than the recommended minimum 0.7 [ 103 ].

In order to analyze the unidimensionality of the scales, an exploratory factor analysis was carried out, which enabled us to group the items and identify five factors or dimensions that explain 70.28% of the total variance (it exceeds the minimum requirement of 50%) ( Table 1 ). The application of this analysis involved the elimination of the item “with this activity I obtain the results I expected” since the factor loading was less than 0.5 [ 106 ].

Perceived service quality: Descriptive statistics and exploratory factor analysis.

* N = 206; Likert scale = 1= least important /5 = most important; 1 Tests that show that the data obtained through the questionnaire were adequate to perform the factor analysis (requirements: Bartlett’s Sphericity Test χ 2 (sig. > 0.05), KMO > 0.7 median, MSA = unacceptable for values below 0.5); 2 S.D: Standard deviation; Source: Authors’ own data.

In the case of the satisfaction scale, the factor analysis resulted in three factors that were denominated (“satisfaction with the facilities”, “satisfaction with the organization of activities”, and “satisfaction with the activity”), which explain 73.77% of the total variance ( Table 2 ). The analysis of the item-total correlation did not involve eliminating any items, since they were higher than 0.3 in all cases.

Satisfaction: Descriptive and factorial exploratory analysis.

* N = 206; Likert scale = 1 = least important /5 = most important; 1 Tests that show that the data obtained through the questionnaire were adequate to perform the factor analysis (requirements: Bartlett’s Sphericity Test χ 2 (sig.> 0.05), KMO > 0.7 median, MSA = unacceptable for values below 0.5); 2 S.D: Standard deviation; Source: Authors’ own data.

From the results of the analyses carried out to corroborate reliability once the item “with this activity I obtain the results I expected” was eliminated in the scale that measures the perceived quality of the service, it can be concluded that the proposed scales are highly reliable, thus being free of random errors, and are able to provide consistent results.

4.2. Regression Analysis

Four multiple regression analyses were proposed in order to corroborate the objectives set. The models included six independent/predictive variables that corresponded to the dimensions included in the scale, enabling us measure the perceived quality of the service (monitor, facilities and material, activities, communication, and staff) with each of the dimensions of satisfaction that have been considered (dependent variable or criterion variable): Overall satisfaction, satisfaction with the facilities, satisfaction with the organization of activities, and satisfaction with the activities. Two control variables were incorporated into the model: Users’ sex and age.

First, the results obtained between the analysis variables in the correlation matrix were analyzed ( Table 3 ). Regarding the control variables, although no significant differences were found and the correlation coefficients are weak, it is observed that the age variable negatively affects the satisfaction with the facilities and with the organization and positively affects the satisfaction with the activities and overall satisfaction. The correlation coefficients allow us to affirm that the dimensions of the perceived quality of the service have a positive relationship with satisfaction (H1, H2, H3, H4), with strong and significant correlation coefficients at the p < 0.01 level.

Measurement scale correlations of the perceived quality of service and user satisfaction.

Note: * p < 0.001. Bilateral test; Source: Authors’ own data.

Prior to the regression analysis, the underlying assumptions on which this type of analysis is based were verified (linearity, independence, homoscedasticity, normality, and noncollaterallity). For the assumption of independence of residuals, the Durbin-Watson statistics was obtained, which, in the three regression models built, gave values between 1.5 and 2.5 ( Table 2 ). In all cases, it gave values lower than 2, which indicates positive autocorrelation.

In the case of collinearity, its diagnosis provided tolerance values between 0.302 and 0.556, which indicate noncollinearity. Therefore, none of the independent variables have correlations greater than 0.9. Moreover, it is possible to assume residual normality, since this tendency could be verified in the analysis of histograms and, in addition, it was confirmed by calculating the Kolmogorov-Smirnov test. Finally, regarding the homoscedasticity assumption, for each value of the independent variables in the scatterplot ( Figure 1 ), the residuals are distributed in a similar way (no relationship was observed between the forecasted values and the residuals).

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Standardized waste. Source: Authors’ own data

In the regression analyses carried out, the measure of the goodness of fit of the model was estimated using the multiple correlation coefficient and the coefficient of determination, which is the square of the previous multiple correlation efficient and expresses the proportion of the variance of the dependent variable explained by the regression model. It is observed that the proposed models have an adequate goodness of fit. In this sense, the explanatory variables contained in the model explain 75.7% of overall satisfaction, 53.4% of the satisfaction with the facilities, 56.1% of the satisfaction with the organization of activities, and 56.0% of the satisfaction with the activity ( Table 4 ). In addition, the F statistic, which enables us to decide whether there is a significant relationship between the dependent variable and the set of independent variables taken together, provides a good adjustment to the point cloud (sig 0.000, indicates that there is a significant linear relationship).

Result of the regression analysis for the dimensions of the perceived quality of the service and satisfaction of the users.

Note: Cell entries are standardized coefficients; * p < 0.05; ** p < 0.001. Bilateral test; Source: Authors’ own data.

Second, the partial correlation coefficient of each explanatory variable was estimated, which indicates the specific relationship of the variable with the dependent variable assuming that the other independent variables remain constant. The sign of the correlation coefficient β makes it possible to determine the direction of the relationship and the F statistic, as well as the goodness of fit of the regression. The p -value (> or < that 1) indicates the significance level with the dependent variable.

The results obtained in the regression together with the correlations enable us to observe that in the case of “general satisfaction”, the dimensions of perceived service quality contribute significantly to explain satisfaction with high and significant β values at a p < 0.001 level. All dimensions, except for the monitor dimension ( p < 0.05), explain satisfaction at a p < 0.001 level. In this sense, the higher the perceived quality of each of the dimensions, the higher the satisfaction experienced by the users.

In this same line, the other three models of multiple regression were proposed with the objective of identifying which dimensions of perceived quality affect the satisfaction that users experience regarding the facilities, organization, and the activities, and to what extent. In the case of satisfaction with the facilities, it is observed that the monitor, the activities, and the staff do not contribute significantly to explain satisfaction (sig > 0.05). As expected, communication significantly contributes to explain satisfaction (β = 0.160, p < 0.05), along with the facilities dimension (β = 0.540, p < 0.001).

The regression model, which explains the satisfaction with the organization of activities, is significantly influenced by the organization of activities (β = 0.399, p < 0.001), staff (β = 0.180, p < 0.001), and communication (β = 0.149, p < 0.001), while the relationship with the facilities and the monitor is not significant (sig > 0.05). Finally, in the last model, which refers to satisfaction with the activities, all the variables are significant at the p < 0.001 level (communication and staff) or p < 0.05 level (monitor and facilities) except for the activities dimension.

Taking the results into account, the hypothesis H1 and, partially, H2, H3, and H4, are corroborated, since not all dimensions positively and significantly influenced satisfaction.

5. Discussion

First, note the results obtained related to the dimension structure of the scale, which enables us to measure the perceived quality of the service. In this research, the rating scale sports organizations (EPOD), developed by Nuviala et al. [ 99 ], was used. Since it was applied to a sample of users of an organization that provides sports services, but with different characteristics from the sample of the original scale, its reliability and unidimensionality were analyzed and studied.

In the case of reliability, Cronbach’s α, which measures the reliability for the total scale, is 0.962, which is very similar to that obtained by Nuviala et al. [ 99 ] of 0.916. If each one of the dimensions is taken into account, it is higher than 0.8 in all cases, corroborating the results obtained by Nuviala et al. [ 99 ] that obtained values between 0.799 and 0.885. Therefore, it was concluded that the scale is reliable.

Regarding the structure of dimensions in this investigation, the items were grouped into six dimensions: Monitor (six items), facilities (five items), sports equipment (four items), activities (nine items), communication (three items), and staff (three items). However, in research by Nuviala et al. [ 99 ], items were grouped into five dimensions (activities, sports experts, spaces, materials, image). The scale measuring satisfaction was divided into three factors or dimensions: Satisfaction with the facilities, with the organization, and with the activity, which correspond to the three scales proposed by Wicker et al. [ 100 ], Nuvialia et al. [ 99 ], and Graupera et al. [ 101 ], and which refer to satisfaction with three aspects or different areas of the sports center, corroborating its reliability.

Once the structure of the considered scales was discussed, the results obtained in this research were discussed relating to the four hypotheses that enabled us to observe the relationships with the quality they perceive and their satisfaction. According to the results, Hypothesis H1 was corroborated, which considered the positive relationship between the dimensions of perceived service quality and overall satisfaction (H1). It was confirmed that the relationship exists (in all cases, the standardized correlation coefficients are significant at the p < 0.001 level). These results, in the case of the relationship with overall satisfaction, are corroborated by empirical studies conducted by Bisschoff and Lotriet [ 107 ], Kyle et al. [ 108 ], Murray and Howat [ 94 ], Shonk and Chelladurai [ 109 ], and Nuviala et al. [ 110 ], which state that a greater level of quality service perception results in greater satisfaction.

Finally, in order to reinforce the validity of the hypotheses and study the relationship structure, different regression models were proposed, which included the perceived service quality dimensions as independent variables and overall satisfaction, satisfaction with the facilities, with the organization, and with the activities as dependent variables, with the purpose of evaluating the joint effects of the independent variables on satisfaction.

The first model showed that the hypothesis H1 was corroborated. All the dimensions of the perceived quality scale influenced satisfaction positively and significantly (on overall satisfaction, p < 0.001), with the variables included in the model explaining 75.7% of satisfaction. This clearly shows that the quality dimensions are closely related to satisfaction, with the most influential variables being facilities and material (β = 0.325, p < 0.001), followed by communication and activity (β = 0.225 and 0.214; p < 0.001). The least influential variables were to HR, monitor, and staff (β = 0.105 and 0.162, p < 0.001). Studies of a quantitative nature corroborate this result. For example, the study carried out by Nuviala et al. [ 110 ], included the perceived value, with 55.6% of satisfaction explained by their model, in addition to the perceived quality dimensions. On the other hand, the dimensions “activities and sports experts” were the most relevant in the regression equation, with β values of 0.347 and 0.266, respectively, with the “value and material” variables being the least important, with a β value of 0.074. These results differ from those obtained in this study. On the contrary, other in the study conducted by Mañas et al. [ 44 ], as well as in this study, it was found that tangible elements are important predictors of user satisfaction.

On the other hand, hypotheses H2, H3, and H4 were partially corroborated. It was observed that in the case of satisfaction with the facilities (H2), the facilities dimension (β = 0.540, p < 0.001) together with communication (β = 0.160, p < 0.05) were the only two dimensions that influenced satisfaction and explained 53.4%. These results show that a center interested in in improving its users’ satisfaction with its facilities must comply with the requirements and expectations of its clients regarding cleanliness, safety, temperature, and sports equipment. In addition, it should pay special attention to the communication mechanisms implemented in its organization. In this sense, the client expects the center to have a procedure of complaints and suggestions, and all those channels necessary to achieve adequate communication with its users.

If the regression model explaining satisfaction with the organization of activities is observed, the independent variables that positively and significantly influenced satisfaction were activities (organization and development), staff, and communication. The users did not consider the dimensions monitor and facilities and material when forming their satisfaction. In the case of satisfaction with the activities, four of the five dimensions influenced satisfaction to a greater or lesser extent, with the exception of the activity dimension, which was not significant (β = 0.095, p > 0.05), while the communication dimension was the most important. The comparison of these results with other studies is complex due to the differences between the measurement instruments used and the dimensions evaluated.

In short, it is observed that the dimensions of perceived quality related to HR (monitor and staff) were the least influential in the satisfaction experienced by the users of the sport and health center, with the dimension facilities and material the most important together with activities and communication, which show a very similar influence. The comparison of these results with other studies is complex due to the differences between the measurements used and the dimensions evaluated.

6. Conclusions

Before starting the presentation of the conclusions, note that this research work is novel since it aims, on the one hand, to fill a gap in research carried out in the sports organizations sector. In this sense, the relationship between perceived service quality and satisfaction has been studied extensively, and this has been corroborated [ 94 , 107 , 108 , 109 ]. However, there is still no consensus on the causality of the relationship, so it is necessary to continue conducting research in this regard [ 91 ].

There are many investigations that develop measurement scales of perceived quality. However, there are very few investigations that analyze which quality dimensions are the most important to form the client’s satisfaction. This research takes into account what was discussed by Szabó [ 111 ] and Tsitskari et al. [ 49 ], who state that the study of quality in the sports industry is in its early stages, so it is essential to continue doing research and deepening knowledge in this area [ 111 ]. In this sense, this research allowed the analysis and reinforcement of some of the conclusions already obtained in other studies.

The results of this investigation have significant academic implications and are of great interest to organizations that provide sports services, enabling the observation of how they jointly affect the dimensions of perceived service quality in the formation of their users’ satisfaction, becoming a key strategic element for any organization. In this sense, it is important to bear in mind that sport and health centers, like any other organization, must improve the quality of the services they provide in order to satisfy their users, and it is necessary to listen to users and measure their satisfaction. This will enable these organizations to adjust their service to the existing demand and to anticipate and adapt to the changes in users’ tastes since, as stated by Súarez et al. [ 112 ] (p. 30), “who determines the quality of a service is the user through his/her satisfaction”.

The first limitation of this study that the study was carried out in a single sport and health center. In future research, the studies should be extended to other sport and health centers, so the results should be extrapolated with caution. Another limitation of this study is its cross section.

Author Contributions

Conceptualization, Investigation, Methodology, Formal Analysis, Writing-Original Draft Preparation and Writing-Review & Editing, J.Á.-G., E.G.-V., M.d.l.C.d.R.-R. and A.D.-S.; Project Administration and Supervision, J.Á.-G. and M.d.l.C.d.R.-R.

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

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Lighting Effects shows how the need for more subjects adds time to a study. This investigation examined whether adjusting the intensity and color of lighting inside the station could help improve crew circadian rhythms, sleep, and cognitive performance. To collect data from enough crew members, the study ran from 2016 until 2020.

Other lengthy studies about how humans adapt to life in space include research on loss of heart muscle and a suite of long-term studies on nutrition, including producing fresh food in space.

Watkins, smiling at the camera, wears a gray sweatshirt, black pants, and black gloves. She floats in space, holding on to a wall with her right hand and gripping an ice-covered black box about the size of a box of tissues. There is a laptop Velcroed to her leg and a lot of cables over her head.

For physical science studies, investigators can send batches of samples to the space station and collect data more quickly, but results can create a need for additional research. Burning and Suppression of Solids ( BASS ) examined the characteristics of a wide variety of fuel samples from 2011 to 2013, and BASS-II continued that work through 2017. The Saffire series of fire safety demonstrations began in 2016 and wrapped up in 2024. Researchers have answered many burning (pun intended) questions, but still have much to learn about preventing, detecting, and extinguishing fires in space.

From left to right, this image has a band of black from top to bottom, a scattering of bright white specks of smoldering cotton like snowflakes, a band of orange flame, a small region of black where the cotton is beginning to char, and a wide band of unburned composite material that appears green because the sample is illuminated with green LED lights.

The timeline for scientific results can run long, especially in microgravity. But those results can be well worth the wait.

Melissa Gaskill International Space Station Research Communications Team Johnson Space Center

Search this database of scientific experiments to learn more about those mentioned above.

1 Macias BR, Liu JHK, Grande-Gutierrez N, Hargens AR. Intraocular and intracranial pressures during head-down tilt with lower body negative pressure. Aerosp Med Hum Perform. 2015; 86(1):3–7. https://www.ingentaconnect.com/content/asma/amhp/2015/00000086/00000001/art00004;jsessionid=31bonpcj2e8tj.x-ic-live-01

2 Powell K. Does it take too long to publish research? Nature 530, pages148–151 (2016). https://www.nature.com/articles/530148a

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Research: What Companies Don’t Know About How Workers Use AI

Jeremie Brecheisen

Three Gallup studies shed light on when and why AI is being used at work — and how employees and customers really feel about it.

Leaders who are exploring how AI might fit into their business operations must not only navigate a vast and ever-changing landscape of tools, but they must also facilitate a significant cultural shift within their organizations. But research shows that leaders do not fully understand their employees’ use of, and readiness for, AI. In addition, a significant number of Americans do not trust business’ use of AI. This article offers three recommendations for leaders to find the right balance of control and trust around AI, including measuring how their employees currently use AI, cultivating trust by empowering managers, and adopting a purpose-led AI strategy that is driven by the company’s purpose instead of a rules-heavy strategy that is driven by fear.

If you’re a leader who wants to shift your workforce toward using AI, you need to do more than manage the implementation of new technologies. You need to initiate a profound cultural shift. At the heart of this cultural shift is trust. Whether the use case for AI is brief and experimental or sweeping and significant, a level of trust must exist between leaders and employees for the initiative to have any hope of success.

Jeremie Brecheisen is a partner and managing director of The Gallup CHRO Roundtable.

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The Loneliness Curve

New research suggests people tend to be lonelier in young adulthood and late life. But experts say it doesn’t have to be that way.

The hand of an elderly person rests on the shoulder of an adolescent.

By Christina Caron

When Surgeon General Vivek Murthy went on a nationwide college tour last fall, he started to hear the same kind of question time and again: How are we supposed to connect with one another when nobody talks anymore?

In an age when participation in community organizations , clubs and religious groups has declined, and more social interaction is happening online instead of in person, some young people are reporting levels of loneliness that, in past decades, were typically associated with older adults.

It’s one of the many reasons loneliness has become a problem at both the beginning and end of our life span. In a study published last Tuesday in the journal Psychological Science, researchers found that loneliness follows a U-shaped curve: Starting from young adulthood, self-reported loneliness tends to decline as people approach midlife only to rise again after the age of 60, becoming especially pronounced by around age 80.

While anyone can experience loneliness, including middle-aged adults , people in midlife may feel more socially connected than other age groups because they are often interacting with co-workers, a spouse, children and others in their community — and these relationships may feel stable and satisfying, said Eileen K. Graham, an associate professor of medical social sciences at the Northwestern University Feinberg School of Medicine and the lead author of the study.

As people get older, those opportunities can “start to fall away,” she said. In the study, which looked at data waves spanning several decades, starting as early as the 1980s and ending as late as 2018, participants at either end of the age spectrum were more likely to agree with statements such as: “I miss having people around me” or “My social relationships are superficial.”

“We have social muscles just like we have physical muscles,” Dr. Murthy said. “And those social muscles weaken when we don’t use them.”

When loneliness goes unchecked, it can be dangerous to our physical and mental health, and has been linked to problems like heart disease, dementia and suicidal ideation.

Dr. Graham and other experts on social connection said there were small steps we could take at any age to cultivate a sense of belonging and social connection.

Do a relationship audit.

“Don’t wait until old age to discover that you lack a good-quality social network,” said Louise Hawkley, a research scientist who studies loneliness at NORC, a social research organization at the University of Chicago . “The longer you wait, the harder it gets to form new connections.”

Studies suggest that most people benefit from having a minimum of four to six close relationships, said Julianne Holt-Lunstad, a professor of psychology and neuroscience and the director of the Social Connection and Health Lab at Brigham Young University.

But it’s not just the quantity that matters, she added, it’s also the variety and the quality.

“Different relationships can fulfill different kinds of needs,” Dr. Holt-Lunstad said. “Just like you need a variety of foods to get a variety of nutrients, you need a variety of types of people in your life.”

Ask yourself: Are you able to rely on and support the people in your life? And are your relationships mostly positive rather than negative?

If so, it’s a sign that those relationships are beneficial to your mental and physical well-being, she said.

Join a group.

Research has shown that poor health, living alone and having fewer close family and friends account for the increase in loneliness after about age 75.

But isolation isn’t the only thing that contributes to loneliness — in people both young and old, loneliness stems from a disconnect between what you want or expect from your relationships and what those relationships are providing.

If your network is shrinking — or if you feel unsatisfied with your relationships — seek new connections by joining a community group, participating in a social sports league or volunteering , which can provide a sense of meaning and purpose, Dr. Hawkley said.

And if one type of volunteering is not satisfying, do not give up, she added. Instead try another type.

Participating in organizations that interest you can offer a sense of belonging and is one way to accelerate the process of connecting in person with like-minded people.

Cut back on social media.

Jean Twenge, a social psychologist and the author of “Generations,” found in her research that heavy social media use is linked to poor mental health — especially among girls — and that smartphone access and internet use “ increased in lock step with teenage loneliness .”

Instead of defaulting to an online conversation or merely a reaction to someone’s post, you can suggest bonding over a meal — no phones allowed.

And if a text or social media interaction is getting long or involved, move to real-time conversation by texting, “Can I give you a quick call?” Dr. Twenge said.

Finally, Dr. Holt-Lunstad suggested asking a friend or family member to go on a walk instead of corresponding online. Not only is taking a stroll free, it also has the added benefit of providing fresh air and exercise.

Take the initiative.

“Oftentimes when people feel lonely, they may be waiting for someone else to reach out to them,” Dr. Holt-Lunstad said. “It can feel really hard to ask for help or even just to initiate a social interaction. You feel very vulnerable. What if they say no?”

Some people might feel more comfortable contacting others with an offer to help, she added, because it helps you focus “outward instead of inward.”

Small acts of kindness will not only maintain but also solidify your relationships, the experts said.

For example, if you like to cook, offer to drop off food for a friend or family member, Dr. Twenge said.

“You’ll not only strengthen a social connection but get the mood boost that comes from helping,” she added.

Christina Caron is a Times reporter covering mental health. More about Christina Caron

Managing Anxiety and Stress

Stay balanced in the face of stress and anxiety with our collection of tools and advice..

How are you, really? This self-guided check-in will help you take stock of your emotional well-being — and learn how to make changes .

These simple and proven strategies will help you manage stress , support your mental health and find meaning in the new year.

First, bring calm and clarity into your life with these 10 tips . Next, identify what you are dealing with: Is it worry, anxiety or stress ?

Persistent depressive disorder is underdiagnosed, and many who suffer from it have never heard of it. Here is what to know .

New research suggests people tend to be lonelier in young adulthood and late life. But experts say it doesn’t have to be that way .

How much anxiety is too much? Here is how to establish whether you should see a professional about it .

Introduction
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Article Information

eTable 1. Descriptive Characteristics for Clinicians in the Survey Analysis, by Standard and Expansion Programs

eTable 2. Regression-Adjusted Total Number of Beneficiaries Who Filled a Prescription for Buprenorphine From National Health Service Corps Clinicians, Pre and Post Expansion, by Loan Repayment Program Group and Beneficiary Characteristic

eMethods 1. Diagnosis Codes

eMethods 2. Medicaid Data Quality

eMethods 3. Survey Questionnaires, Response Rates, Methodology

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Rowan K , Shah SV , Binns S, et al. Buprenorphine Prescribing and Challenges Faced Among National Health Service Corps Clinicians. JAMA Netw Open. 2024;7(5):e2411742. doi:10.1001/jamanetworkopen.2024.11742

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Buprenorphine Prescribing and Challenges Faced Among National Health Service Corps Clinicians

1 NORC at the University of Chicago, Bethesda, Maryland
2 Health Resources and Services Administration Bureau of Health Workforce, Rockville, Maryland

Question What is the association between the National Health Service Corps (NHSC) Loan Repayment Program (LRP) expansion and access to medication for opioid use disorder (MOUD), and what challenges to providing MOUD may NHSC clinicians and sites continue to face?

Findings In this cross-sectional study of Medicaid claims data for 7828 NHSC clinicians and survey data from 3297 clinicians and 4732 sites, at least 123 422 additional Medicaid beneficiaries were provided with MOUD over the first 2.5 years following the LRP expansion. However, 70% of clinicians reported a lack of addiction counseling to accompany treatment with MOUD as well as other staffing shortages.

Meaning These findings suggest that additional clinicians and training are needed to increase access to comprehensive treatment with MOUD.

Importance The National Health Service Corps (NHSC) Loan Repayment Program (LRP) expansion in fiscal year (FY) 2019 intended to improve access to medication for opioid use disorder (MOUD) by adding more clinicians who could prescribe buprenorphine. However, some clinicians still face barriers to prescribing, which may vary between rural and nonrural areas.

Objective To examine the growth in buprenorphine prescribing by NHSC clinicians for Medicaid beneficiaries during the NHSC LRP expansion and describe the challenges to prescribing that persist in rural and nonrural areas.

Design, Setting, and Participants This cross-sectional study analyzed preexpansion and postexpansion Medicaid claims data to evaluate the percentage of prescriptions of buprenorphine filled during FY 2017 through 2021. This study also analyzed challenges and barriers to prescribing MOUD between rural and urban areas, using results from annual surveys conducted with NHSC clinicians and sites from FY 2019 through FY 2021.

Exposure Prescribing of buprenorphine by NHSC clinicians.

Main Outcomes and Measures The main outcomes were the percentage and number of Medicaid beneficiaries with opioid use disorder (OUD) who filled a prescription for buprenorphine before and after the LRP expansion and the challenges NHSC clinicians and sites faced in providing substance use disorder and OUD services. Survey results were analyzed using descriptive statistics.

Results During FYs 2017 through 2021, 7828 NHSC clinicians prescribed buprenorphine (standard LRP: mean [SD] age, 38.1 [8.4] years and 4807 females [78.9%]; expansion LRPs: mean [SD] age, 39.4 [8.1] years and 1307 females [75.0%]). A total of 3297 NHSC clinicians and 4732 NHSC sites responded to at least 1 survey question to the 3 surveys. The overall percentage of Medicaid beneficiaries with OUD who filled a prescription for buprenorphine during the first 2.5 years post expansion increased significantly from 18.9% before to 43.7% after expansion (an increase of 123 422 beneficiaries; P < .001). The percentage more than doubled among beneficiaries living in areas with a high Social Vulnerability Index score (from 17.0% to 36.7%; an increase of 31 964) and among beneficiaries living in rural areas (from 20.8% to 55.7%; an increase of 45 523). However, 773 of 2140 clinicians (36.1%; 95% CI, 33.6%-38.6%) reported a lack of mental health services to complement medication for OUD treatment, and 290 of 1032 clinicians (28.1%; 95% CI, 24.7%-31.7%) reported that they did not prescribe buprenorphine due to a lack of supervision, mentorship, or peer consultation.

Conclusions and Relevance These findings suggest that although the X-waiver requirement has been removed and Substance Abuse and Mental Health Services Administration guidelines encourage all eligible clinicians to screen and offer patients with OUD buprenorphine, as permissible by state law, more trained health care workers and improved care coordination for counseling and referral services are needed to support comprehensive OUD treatment.

The opioid epidemic in the US continues to claim more than 100 000 lives annually, and in 2021, it accounted for 75% of all overdose deaths. 1 The total annual number of deaths from opioid overdose has more than doubled between 2015 and 2021, from 52 623 to 107 573. 2

Buprenorphine is a long-standing, evidence-based treatment for patients with opioid use disorder (OUD), though it may still be underused. 3 - 6 To expand access to medication for OUD (MOUD), the US Congress repealed the X-waiver requirement in December 2022, and the Drug Enforcement Administration (DEA) and Substance Abuse and Mental Health Services Administration issued new guidelines that have increased the flexibility in the training required for prescribing buprenorphine and removed restrictions on the number of patients physicians can treat. 7 In May 2023, the DEA also extended flexibilities in using telehealth for prescribing buprenorphine that were enacted during the COVID-19 pandemic. 8

While these changes have the potential to expand treatment for OUD, clinicians still face challenges and barriers to providing MOUD, including a lack of resources for consultation, stigma, and insufficient education and training. 5 , 9 , 10 Access to MOUD in rural areas is also hampered by the shortage of clinicians in medically underserved areas (ie, areas with limited access to health care). 11 , 12

To help combat the opioid crisis in underserved areas, the Health Resources and Services Administration (HRSA) expanded the National Health Service Corps (NHSC) Loan Repayment Program (LRP) to include 2 new programs, the Substance Use Disorder (SUD) LRP and Rural Community LRP (referred to as expansion LRPs in this study), in addition to the existing standard LRP. The NHSC LRP offers primary care, dental, and behavioral health care clinicians the opportunity to have their student loans repaid while working at NHSC sites, which are health care facilities located in underserved communities. These 2 expansion programs emphasize the recruitment of clinicians trained in SUD treatment, whereas the standard program is targeted more for primary care clinicians. The expansion programs require a longer commitment of 3 vs 2 years compared with the standard program, and clinicians in the SUD and Rural Community LRPs receive higher levels of loan payment ($75 000 and $100 000, respectively, compared with $50 000 in the standard program).

Prior work, 13 conducted as part of an independent evaluation of HRSA’s SUD investments, described the role of the NHSC in expanding behavioral health services in socially vulnerable and rural areas but did not address the expansion of buprenorphine for treatment of OUD or challenges clinicians faced in providing OUD treatment. This prior analysis, conducted with fiscal year (FY) 2019 NHSC clinicians (the first year of the expansion programs), showed that the percentage of NHSC clinicians working in rural areas increased by 59% between FY 2017 and FY 2020. It also showed that 66% (962 of 1562) of NHSC sites added or expanded MOUD, including buprenorphine, methadone, and naltrexone.

The literature on strategies to improve substance use treatment in rural and underserved areas is limited. 14 As OUD continues to be a substantial public health problem that affects families and communities across the country, addressing persistent challenges through policy options and actions at the state and federal levels may help to mitigate the opioid and substance use epidemic. Thus, the aims of this study are to analyze buprenorphine prescribing for Medicaid beneficiaries, particularly those living in rural and socially vulnerable communities, by NHSC clinicians since the LRP expansion and to describe the challenges and barriers to OUD treatment that may persist since removal of the DEA waiver requirement.

In this cross-sectional study, which is part of the larger evaluation, 13 the analytic population consisted of new NHSC clinicians (new LRP awardees in FY 2019 through FY 2021) and all NHSC sites (FY 2019 through FY 2021). All new clinicians and sites were eligible to participate in the evaluation surveys. The claims analysis was conducted on a subset of the NHSC clinicians who were physicians, nurse practitioners, and physician assistants who prescribed buprenorphine to Medicaid beneficiaries. The National Opinion Research Center’s institutional review board reviewed all aspects of the study’s data collection and determined the study not to be human participants research under Federalwide Assurance No. FWA00000142. The use of clinician and beneficiary claims data complied with a data use agreement through the Centers for Medicare & Medicaid Services Research Data Assistance Center to ensure privacy. Evaluation survey respondents were shown a screen stating that by starting the survey, they agreed to participate in the survey. This study follows the Strengthening the Reporting of Observational Studies in Epidemiology ( STROBE ) reporting guideline for cross-sectional studies.

We used clinicians’ National Provider Identifiers (NPIs), available from the NHSC application data obtained from HRSA, to identify them in claims data in the preexpansion and postexpansion periods. Assignment to the standard or expansion groups in these analyses was determined by which 1 of the 3 programs NHSC clinicians selected on their applications. Application data collected included self-reported demographic measures of gender (female, male, and does not wish to disclose), age, underrepresented minority status as reported by HRSA (includes individuals identifying as American Indian or Alaska Native, Black or African American, Native Hawaiian or Other Pacific Islander, and Hispanic [all races]), 15 and program assignment (standard, SUD, or Rural Community LRP).

For the claims analyses, we grouped clinicians in the 2 expansion programs (SUD and Rural Community) together to enable a comparison to the standard program. We also used 3 years of pooled cross-sectional data from surveys (fielded by the authors) on NHSC clinicians and sites. Survey respondents included NHSC clinicians and sites who answered at least 1 question examined in this study.

Transformed Medicaid Statistical Information System data were used to determine the percentage and number of beneficiaries with OUD who filled a prescription. Almost 40% of adults aged 18 to 64 years with OUD have health care through Medicaid. 16 Claims were analyzed for the 2.5 years before (January 1, 2017, to June 30, 2019) and after (July 1, 2019, to December 31, 2021) the NHSC program expansion. The algorithm for medication-assisted treatment from the Medicaid Section 1115 Substance Use Disorder Demonstrations: Technical Specifications for Monitoring Metrics , version 4.0 manual 17 was used to identify beneficiaries with OUD and a prescription. This algorithm includes all beneficiaries with an OUD diagnosis who were enrolled in Medicaid for any amount of time during the measurement period as the denominator. Beneficiaries were classified as having OUD if they had at least 1 claim with a diagnosis code listed under the Healthcare Effectiveness Data and Information Set 2019 Opioid Abuse and Dependence Value Set in the past 12 months (complete list provided in eMethods 1 in Supplement 1 ). We reviewed the quality of the Medicaid prescription claims using the Medicaid Data Quality Atlas; each topic of prescription claims received a quality rating (low, medium, high, or unusable). 18 We used data from all states in all years, acknowledging that data for 2 states would be undercounted (Florida and Maine) due to a high level of incompleteness or missing a prescribing NPI (details provided in eMethods 2 in Supplement 1 ). For claims with a missing prescribing date (approximately 6.8%), we used the fill date because we observed that for prescriptions with both dates, the mean (SD) time between prescription and fill was 3.5 (11.7) days. We included all forms of prescription buprenorphine (eg, alone or in combination with naloxone).

To understand changes in buprenorphine use for beneficiaries living in rural areas and areas with high social vulnerability, we used county-level rural classification data from the Federal Office of Rural Health Policy to identify beneficiaries living in rural areas. 19 We also referred to HRSA’s definition of rural as all nonmetropolitan counties, all metropolitan census tracts with Rural Urban Commuting Area codes 4 to 10, and large-area metropolitan census tracts of at least 400 square miles in areas with a population density of 35 or less per square mile with Rural Urban Commuting Area codes 2 to 3. 20 We used county-level Social Vulnerability Index (SVI) data from the Centers for Disease Control and Prevention’s Agency for Toxic Substances and Disease Registry to identify and classify counties in the highest quintile of SVI scores, indicating the greatest social vulnerability. 21

We conducted 3 cross-sectional surveys of new NHSC clinicians (new LRP awardees in FY 2019 through FY 2021) and NHSC sites (FY 2019 through FY 2021) in the fall of each year during 2020 to 2022. Both the NHSC clinician and site surveys included questions about challenges to providing SUD and OUD services. With the organizations’ institutional review board approval, we used NHSC administrative data to identify clinicians and sites in rural areas. The surveys and related materials were approved by the US Office of Management and Budget, and links to the survey materials and more details on the survey development and fielding are provided in eMethods 3 in Supplement 1 .

We provide descriptive statistics on demographic characteristics of clinicians in the analysis. Demographic measures are reported separately for clinicians in the claims analyses (which are stratified by standard and expansion programs) and for clinicians in the survey analyses (which are stratified by rural and nonrural areas). We provide characteristics for clinicians in the survey analyses by standard and expansion programs in eTable 1 in Supplement 1 .

We calculated the percentage and number of total Medicaid beneficiaries with OUD with a prescription for buprenorphine in the preexpansion and postexpansion period from claims data. National Provider Identifiers were used to identify NHSC clinicians in the preexpansion and postexpansion period. To test whether the number of beneficiaries increased significantly more among clinicians who joined the expansion LRPs compared with the standard LRP, a difference-in-differences framework was used, with an interaction term for the expansion program in the postexpansion period, using a negative binomial regression model (to account for the overdispersion of the data) adjusted for the number of clinicians by discipline.

Using the survey data, we computed descriptive statistics (proportion and frequency) on measures of challenges that NHSC clinicians and sites faced in providing SUD and OUD treatment. We tested for significant differences in survey outcomes (2-sided P < .05) between rural and nonrural areas using bivariate logistic regression. We used an unadjusted model, since the aim of this study was to describe the prevalence of challenges among NHSC clinicians and sites and differences between rural and nonrural areas, rather than constructing a multivariable model to examine correlates of these challenges. We used the Benjamini-Hochberg method to implement a false discovery rate correction for multiple comparisons. 22 Since survey responses may be correlated within sites, we also examined the intraclass correlation coefficients for each survey question using a multilevel model. We observed very small intraclass correlation coefficients for the 4 questions in the analysis (0.016, 0.005, 0.004, and 0.001, respectively) and, therefore, did not cluster the SEs at the site level. All analyses were conducted using Stata, version 16 software (StataCorp LLC).

Table 1 provides the descriptive statics of the clinicians in the claims analysis (1743 in the expansion LRPs and 6085 in the standard LRP) and the survey respondents (3297, including 1304 in rural sites and 1993 in nonrural sites). For the claims analysis, which compared buprenorphine prescribing between clinicians in the expansion programs vs the standard program, the programs included more advanced practice nurses (67.4% [1168] vs 57.6% [3529]), fewer physicians (19.0% [331] vs 23.4% [1400]), fewer physician assistants (13.6% [244] vs 19.1% [1156]), fewer women (75.0% [1307] vs 78.9% [4807]), and fewer individuals with an underrepresented minority status (21.3% [366] vs 29.2% [1765]). The mean (SD) age was 39.4 (8.1) years in the expansion LRPs vs 38.1 (8.4) years in the standard program, and distributions were similar for male (expansion, 418 [24.0%]; standard, 1278 [21.1%]) and nondisclosed (expansion, 18 [1.0%]; standard, 0) gender. In the survey analysis, which compared clinicians in rural and nonrural sites, the rural sites had fewer physicians (13.4% [175] vs 16.2% [322]), fewer dentists (0.6% [9] vs 1.6% [32]), more pharmacists (2.8% [36] vs 0.9% [18]), and fewer individuals with an underrepresented minority status (12.1% [157] vs 26.4% [526]). Age and gender distributions between rural and nonrural respondents were similar (rural: mean [SD] age, 39.9 [9.3] years; 311 men [23.9%], 985 women [75.5%], and 8 who did not disclose [0.6%]; nonrural: mean [SD] age, 39.2 [8.8] years; 460 men [23.1%], 1518 women [76.1%], and 15 who did not disclose [0.8%]).

Table 2 reports the percentage and total number of beneficiaries who filled at least 1 prescription for the standard and expansion LRPs in the preexpansion and postexpansion periods for individuals with OUD overall, individuals with OUD living in rural areas, and individuals with OUD living in areas with a high SVI score. The preexpanison period reflects claims data from NHSC clinicians who were already working in the standard program or who later entered an expansion program. There was substantial growth in the percentage of beneficiaries who filled prescriptions in both the standard and expansion LRPs, but the growth was significantly larger among clinicians in the expansion LRPs (difference in differences, 7175.5; 95% CI, 4895.7-9455.3; P < .001) (eTable 2 in Supplement 1 shows the regression results). During the 2.5 years following the expansion, the percentage of beneficiaries with OUD who filled a prescription increased from 18.9% to 43.7%, or 123 422 additional beneficiaries. Of this increase, 73.0% was attributed to NHSC clinicians in the expansion programs (90 040 beneficiaries). An additional 45 523 beneficiaries with OUD living in rural areas (an increase from 20.8% to 55.7%) and an additional 31 964 beneficiaries with OUD (an increase from 17.0% to 36.7%) living in areas with a high SVI score filled prescriptions in the postexpansion period. Of beneficiaries living in rural areas and areas with a high SVI score, 71.0% filled prescriptions from clinicians in the expansion LRPs in the postexpansion period.

Table 3 reports challenges to SUD and OUD treatment for clinicians and sites in rural and nonrural areas. The greatest challenge among NHSC clinicians providing SUD treatment was limited treatment resources, such as referrals to counselors and detoxification programs (2108 of 3113 [67.7%; 95% CI, 65.6%-69.7%]); this challenge was significantly higher for rural compared with nonrural clinicians (964 of 1303 [74.0%; 95% CI, 70.8%-76.9%] vs 1144 of 1810 [63.2%; 95% CI, 60.4%-66.0%], a 10.8–percentage point difference). Limited treatment resources was the second most common challenge reported among NHSC sites (1997 of 4732 [42.1%; 95% CI, 40.7%-43.5%]); this challenge was also significantly higher among rural sites compared with nonrural sites (1164 of 2498 [46.6%; 95% CI, 39.0%-48.5%] vs 827 of 2234 [37.0%; 95% CI, 35.0%-39.0%], a 9.6–percentage point difference). A lack of trained staff was the second most common challenge reported by clinicians (1725 of 3113 [55.4%; 95% CI, 53.2%-57.6%]) and the greatest challenge reported by sites (2206 of 4732 [46.5%; 95% CI, 45.1%-48.0%]), with higher rates among clinicians (though not significantly, after adjusting for multiple comparisons) and sites in rural areas compared with nonrural areas (4.0 percentage points higher among rural sites). Limited access to OUD treatment options was reported by 1286 of 3113 clinicians (41.3%; 95% CI, 39.1%-43.4%) and was 11.4 percentage points higher among rural clinicians compared with nonrural clinicians. In addition, 968 of 4732 sites (20.4%; 95% CI, 19.3%-21.6%) reported limited OUD treatment options, with a significantly higher rate among rural sites vs nonrural sites (607 of 2498 [24.3%; 95% CI, 17.7%-26.1%] vs 362 of 2234 [16.2%; 95% CI, 14.7%-17.7%], an 8.1–percentage point difference).

Respondents who reported limited access to OUD treatment options as a challenge were asked which specific services were lacking or limited at their site ( Table 4 ). The top responses for both clinicians and sites were addiction counseling (882 of 1254 clinicians [70.3%; 95% CI, 67.0%-73.4%] and 566 of 937 sites [60.3%; 95% CI, 57.2%-63.4%]) and access to MOUD (780 of 1254 clinicians [62.2%; 95% CI, 58.7%-65.4%] and 637 of 937 sites [67.9%; 95% CI, 64.8%-70.8%]). We did not find significant differences between rural and nonrural clinicians for these outcomes. Significantly more rural NHSC sites compared with nonrural sites reported a lack of addiction counseling (378 of 591 [64.0%; 95% CI, 59.5%-67.7%] vs 188 of 346 [54.3%; 95% CI, 49.0%-59.5%], a 9.7–percentage point difference) and diagnosis by licensed professionals (371 of 591 [62.8%; 95% CI, 59.8%-66.6%] vs 189 of 346 [54.6%; 95% CI, 49.3%-59.8%], an 8.2–percentage point difference).

Table 5 shows survey results for challenges to prescribing buprenorphine among clinicians eligible to prescribe and reasons why they did not prescribe. We did not find significant differences between clinicians working in rural and nonrural areas. The greatest challenge was concern over medication diversion or misuse (929 of 2140 [43.4%; 95% CI, 40.8%-46.1%]), while the second greatest challenge was a lack of mental health services to complement MOUD (773 of 2140 [36.1%; 95% CI, 33.6%-38.6%]). Lack of supervision and the ability to consult peers on prescribing as a challenge was reported by 400 of 2140 clinicians (18.7%; 95% CI, 16.7-20.9).

A total of 1032 clinicians indicated they did not prescribe buprenorphine, even though it was within the scope of their current role. The most common reason given by both rural and nonrural clinicians was a lack of supervision, mentorship, or peer consultation (290 [28.1%; 95% CI, 24.7%-31.7%]). Organizational factors (eg, policies around initiation of treatment and a zero tolerance for continued drug use) were the second most common reason for not prescribing among all clinicians (269 [26.1%; 95% CI, 22.8%-29.7%]). Clinicians working in rural areas were significantly more likely than nonrural clinicians to report a lack of other mental health services to complement medication (69 of 369 [18.6%; 95% CI, 14.0%-24.2%] vs 83 of 663 [12.5%; 95% CI, 9.6%-16.1%], a 6.1–percentage point difference).

This cross-sectional study found that the NHSC LRP expansion was associated with an increase in the percentage of Medicaid beneficiaries with OUD who were prescribed buprenorphine. More than 3 times as many beneficiaries overall, and 3.8 times as many beneficiaries in rural areas, received a prescription in the 2.5-year period following the expansion than in the preceding 2.5-year period. Clinicians reached more beneficiaries in rural areas and areas with high SVI scores, indicating that the NHSC program expansion contributed to the recruitment and placement of clinicians in high-need areas.

However, our findings show that continued expansion in OUD treatment may be hampered by inadequate counseling resources to support MOUD, a lack of trained staff, and limited availability of peers or supervisors to assist clinicians in prescribing and treating OUD. Among the clinicians who reported limited access to OUD treatment options, patient access to addiction counseling was the largest barrier reported by clinicians (70.3%). Just over one-third (36.1%) of clinicians reported that a lack of mental health services to complement medication use was the greatest challenge to OUD treatment and a reason expressed by 1 in 8 clinicians (14.7%) for not prescribing MOUD. Our results reflect survey data collected during the COVID-19 pandemic when the health care workforce faced substantial attrition and burnout; however, the high rates of respondents indicating limited personnel to support MOUD suggest the need to continue to train and retain behavioral health care workers in underserved areas. 23 For example, HRSA estimates that since 2021, demand for behavioral health clinicians (ie, addiction counselors, psychiatrists, social workers, and therapists) has increased by 8%, and supply has decreased by 2%. 24 This workforce shortage may stem from a long history of regulatory constraints on clinician capacity to prescribe MOUD, including the X-waiver’s requirements regarding the clinician’s training hours and number of patients. However, the removal of the waiver does not address the challenges to team-based OUD treatment observed in this study, limited addiction training during medical education, and stigma around the effectiveness of MOUD. 23

Strategies to expand MOUD delivery require an adequate supply of behavioral health clinicians and other nonprescribing health care workers to help patients transition across settings. 25 Federal programs that expand the number of behavioral health clinicians and create incentives to work in underserved areas, including the NHSC LRPs and HRSA grant programs such as the Behavioral Health Workforce Education and Training program, could play an essential role in building and retaining the nation’s behavioral health workforce.

This study has several limitations. The significant increase in the number of Medicaid beneficiaries with OUD who had a prescription for buprenorphine cannot be attributed solely to NHSC expansion, as during the study period, both federal and state policies were enacted to improve access to buprenorphine, including enabling telehealth for prescribing and increasing patient panel sizes, and studies have shown that these changes had some effect. 26 , 27 In addition, our findings are not stratified at the state level, and state-level policies and guidelines can facilitate or limit prescribing. Medicaid data quality also varies by state, and claims data only reflect filled prescriptions. Because of incomplete claims, missing prescriber NPIs, or unfilled prescriptions, the results may undercount all prescriptions written by NHSC clinicians. We cannot quantify the number of unfilled prescriptions, and we were not able to locate prior research that examined what percentage of prescriptions for buprenorphine remain unfilled among Medicaid beneficiaries. The study was conducted before the removal of the X-waiver in December 2022; thus, future research should continue to study the persistence of challenges to prescribing and comprehensive treatment, as well as the variation in challenges across states, as policies continue to evolve. The findings also reflect results among NHSC clinicians and sites and may not be generalizable to the challenges faced by clinicians who do not work in underserved areas. While it may be possible that some NHSC clinicians were newly licensed recent graduates and did not prescribe buprenorphine before they entered the NHSC LRP, the mean age of the prescribing clinicians was 38 years, which suggests that most were not recent graduates. One reason for discrepancies between NHSC clinician and site reports of perceived challenges is that NHSC sites may have more than 1 facility, and site respondents were asked to summarize their responses across all facilities.

This cross-sectional study found that the LRP expansion was associated with increases in access to buprenorphine. These findings also suggest that clinicians and care teams may need continued training, mentorship, staffing, and connections to referral networks to provide appropriate, comprehensive SUD and OUD treatment.

Accepted for Publication: March 15, 2024.

Published: May 17, 2024. doi:10.1001/jamanetworkopen.2024.11742

Corresponding Author: Kathleen Rowan, PhD, NORC at the University of Chicago, 4350 East-West Hwy, 8th Floor, Bethesda, MD 20814 ( [email protected] ).

Author Contributions: Drs Rowan and Shah had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Rowan, Shah, Binns, Murphy, Robbins, Schoebel, Knudson, Kepley.

Acquisition, analysis, or interpretation of data: Rowan, Shah, Murphy, Satorius, Ghobadi, Krauss, Schoebel, Knudson.

Drafting of the manuscript: Rowan, Shah, Binns, Murphy, Ghobadi, Kepley.

Critical review of the manuscript for important intellectual content: Rowan, Shah, Satorius, Krauss, Robbins, Schoebel, Knudson, Kepley.

Statistical analysis: Rowan, Shah, Krauss.

Obtained funding: Rowan, Knudson, Kepley.

Administrative, technical, or material support: Shah, Binns, Murphy, Satorius, Ghobadi, Robbins, Schoebel, Kepley.

Supervision: Rowan, Shah, Robbins, Knudson, Kepley.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was funded under contract HSH250201300021I 75R60219F34012 from the Health Resources and Services Administration.

Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; and the preparation, review, approval, or decision to submit the manuscript.

Group Information: A full list of the members of the Bureau of Health Workforce Substance Use Disorder Evaluation Team who contributed to this analysis appears in Supplement 2 .

Data Sharing Statement: See Supplement 3 .

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Schumer’s long-awaited AI ‘road map’ is coming this week. It will cost billions.

Crafted by a bipartisan group of senators, the plan reviews a host of issues — including AI’s effect on the military, health care and workers. It could be released as soon as Tuesday.

A bipartisan group of senators, including Majority Leader Charles E. Schumer, will unveil a long-awaited “road map” this week for regulating artificial intelligence, directing Congress to infuse billions of dollars into research and development of the technology while addressing its potential harms.

The sprawling directive comes almost a year after Schumer (D-N.Y.) called for an “all hands on deck” push to regulate AI, saying Congress needed to accomplish years of work in months.

While not legislation, the initiative is intended to provide direction to the Senate committees increasingly crafting bills tackling the technology. The plan reviews a host of issues — including AI’s effect on the military, health care and workers, according to people who have been briefed on the plan, who spoke on the condition of anonymity to discuss the unreleased document. The plan could be made public as soon as Tuesday, one of the people said.

“The road map is still being finalized and should be released shortly,” Schumer spokeswoman Allison Biasotti said in a statement.

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The plan is expected to call for about $32 billion in funding for AI research and development, according to people familiar with it. The figure is based on a 2021 National Security Commission on Artificial Intelligence report, which called for 1 percent of U.S. gross domestic product to be directed to research and development at agencies including the Department of Energy, the National Science Foundation, and the National Institute of Standards and Technology.

The plan will also call for individual sectors — such as health care — to develop specific rules for AI, as well as for the development of testing and transparency measures that will help explain potential harms of the technology. The document will also include provisions to ensure that the U.S. military stays competitive in AI, tracking adversaries’ progress in developing the technology.

The United States lags far behind Europe and other governments in crafting guidelines for AI, and the road map is intended to spur a wave of legislative activity in Congress. The plan has bipartisan backing, but many observers are skeptical that a deeply polarized legislature will be able to craft comprehensive AI laws during a heated presidential election year.

Meanwhile, U.S. tech companies are forging ahead with ever more powerful AI systems and tools. OpenAI on Monday announced a number of upgrades to ChatGPT, powered by a new model that improves the chatbot’s capabilities to listen and respond by voice. Google is expected to announce AI enhancements to its own products at its Tuesday developer conference.

Schumer has urged the United States to swiftly develop guardrails for AI. A bipartisan group of senators dubbed the “AI Gang” — including Sens. Martin Heinrich (D-N.M.), Mike Rounds (R-S.D.) and Todd Young (R-Ind.) — crafted the proposal.

The plan is also expected to call for the passage of bipartisan bills that have already been introduced, including the Create AI Act, which would establish federal infrastructure for AI research, one of the people said. It also includes provisions to promote training and developing workers for other skills, amid broad concerns about the effect artificial intelligence could have on jobs, another of the people said.

Schumer teased the upcoming plan during an interview last week at the AI Expo for National Competitiveness , where he said congressional committees will take the lead on recommendations in the document. Some committees will move faster than others, he said. The Rules Committee, helmed by Sen. Amy Klobuchar (D-Minn.), is scheduled Wednesday to consider three bipartisan bills to address the effect of artificial intelligence on U.S. elections.

“Our committees will go to work,” Schumer said. “Some committees are a little further along than others. We’re not going to wait to have one huge comprehensive plan that touches on everything.”

Schumer’s plan is a product of months of meetings among lawmakers, top tech executives, civil rights and labor leaders, consumer protection advocates, and researchers, through a series of sessions he dubbed “insight forums.” In the most high-profile gathering last year, Schumer held a six-hour session with executives locked in fierce competition to direct the future of AI development, including Tesla CEO Elon Musk, Meta CEO Mark Zuckerberg and OpenAI CEO Sam Altman.

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