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This study empirically tested the Sport Website Acceptance Model (SWAM), proposed by Hur, Ko and Claussen (2007). The SWAM added Perceived Enjoyment (Davis et al, 1992) and Perceived Trustworthiness (Belanger et al, 2002) to the two factors Perceived Ease of Use and Perceived Usefulness used in the Technology Acceptance Model (TAM) (Davis, 1989). This study proposes a competing model to the original SWAM and compares this by incorporating two additional constructs, Sport Involvement (Shank & Beasley, 1998) and Psychological Commitment to a Team (Mahony et al, 2000). Structural equation modeling analyses revealed acceptable model fits, both in the original SWAM and in the competing model. Subsequent analyses led the authors to conclude that the competing model was the better version of the SWAM.

The purpose of this paper is to analyze the dependent competing failure reliability of harmonic drive (HD) with strength failure and degradation failure.

Based on life tests and stiffness degradation experiments, Wiener process is used to establish the accelerated performance degradation model of HD. Model parameter distribution is estimated by Bayesian inference and Markov Chain Monte Carlo (MCMC) and stiffness degradation failure samples are obtained by a three-step sampling method. Combined with strength failure samples of HD, copula function is used to describe the dependence between strength failure and stiffness degradation failure.

Strength failure occurred earlier than degradation failure under high level accelerated condition; degradation failure occurred earlier than strength failure under medium- or low-level accelerated condition. Gumbel copula is the optimum copula function for dependence modeling of strength failure and stiffness degradation failure. Dependent competing failure reliability of HD is larger than independent competing failure reliability.

The reliability evaluation method of dependent competing failure of HD with strength failure and degradation failure is first proposed. Performance degradation experiments during accelerated life test (ALT), step-down ALT and life test under rated condition are conducted for Wiener process based step-down accelerated performance degradation modeling.

The topic of organizational culture has attracted the attention of numerous researchers from both quantitative and qualitative perspectives. A review of the literature shows that the quantitative assessment of organizational culture has been dominated by studies adopting the competing values framework developed by Quinn and his colleagues. The use of this model embraces the notion that the 4 cultural types depicted by the framework can be used not only to represent the culture of an organization but also to serve as a basis upon which one organization can be differentiated from others. Various attempts have been reported to support the validity of the framework for describing the culture of an organization; however, the claim that one organization can be differentiated from another on the basis of the 4 cultural types is yet to be empirically supported. The study reported here set out to show that the competing values model can be used to differentiate organizations from one another. Based on a survey administered to all academic staff in 7 out of the 8 government‐funded higher education institutions in Hong Kong, the study successfully confirmed the validity of the competing values model as a tool in differentiating organizations.

Despite an extensive body of research on brand loyalty, it has been demonstrated that customer‐based brand research is still in a state of evolution. The purpose of this paper is to develop and test alternative models of the brand loyalty process by examining the effects of customer orientation, brand association, perceived service quality, and satisfaction on brand loyalty utilizing data from South Korea and China. Further, relatively little attention has been given to the competing process of individual‐level brand loyalty. Thus, this paper aims to examine the relationships among satisfaction and other key constructs that may potentially affect brand loyalty.

Structural equation analysis of six competing models is provided. Although competing models are supported by prior research, they differ with respect to the particular mechanism that underlies the alternative explanations and the mediating effects. In this study, Armstrong's notion is adopted to show that the role of the scientist is changed from advocating a single hypothesis to evaluating which of a number of competing models is more appropriate. The current research attempts to empirically test competing mechanisms pertaining to how each of the variables affects brand loyalty.

First, the research model fits well and outperforms other competing models. Second, the results are consistent with the proposed model even though there are cultural differences between Chinese and South Korean consumers. Finally, the research model empirically establishes the mediating role of satisfaction in the context of brand loyalty formation.

This study is a contribution to extant research because it empirically establishes the inter‐relationships between important variables affecting brand loyalty (e.g. customer orientation, satisfaction, and perceived quality) across two cultures (South Korea and China), thus further enhancing the efficacy of the obtained results.

The article aims to focus on the debate around the interplay between product innovation and servitization. Two conflicting approaches characterize the debate, disagreeing as to whether product innovation and servitization are complementary or not.

The authors examine two competing models proposing a direct effect of product innovation on servitization and an indirect effect through digitalization, using the sample of 500 manufacturing firms of a country participating in the European Manufacturing Survey, 2018 edition.

The results reveal that product innovation has no direct effect on servitization. However, the authors found that digitalization capabilities mediate the effect of product innovation and servitization. The present findings reveal that product innovation has a substantial indirect effect on servitization through digitalization capabilities, supporting the approach proposing the complementarity between product innovation and servitization.

The data used in this paper correspond to a single country. The limited geographical sampling frame may likewise limit the generalizability of the findings. Researchers are encouraged to replicate the analysis with data from other countries, and to further enrich the analysis with complementary path options and resulting performance measures.

When applying a capabilities perspective, the authors find that product innovation capability is not directly related to servitization as capability. The present findings point toward the fact that if companies only have product innovation capability, this does not facilitate servitization. If companies have both product innovation capability and digitalization capability, such a situation facilitates servitization, a decision which often falls within managers’ responsibilities.

Existing studies focus on antecedents and/or outcomes of single issues, either product innovation, servitization or digitalization. Only some offer dual associations (product innovation and servitization, digitalization and servitization), and even less position simultaneously at the intersection of the three pillars. Herein lies the novelty of the present approach and analysis, which explains the extent to which product innovation, digitalization and servitization are related.

The purpose of this paper is to apply duration methods to a sample of Farm Service Agency (FSA) direct, seven‐year operating loans to identify those variables that influence the time to loan termination and type of termination. Variables include both those known at time of loan origination and those that characterize the changing economic environment over the life of the loan. Also, to examine the impact of various FSA programs promoting policy objectives.

A systematic sample of 877 seven‐year, FSA direct loans originated between October 1, 1993 and September 30, 1996 was collected. Cox regression, competing risks models are estimated as a function of borrower and loan characteristics observable at loan origination. Economic indicator variables emphasizing the farm economy and observed quarterly over the life of the loan are also included as explanatory variables.

Loan characteristics, borrower financial characteristics and degree of borrower interaction with FSA observable at origin are significant variables in determining type of loan outcome (default or paid‐in‐full) and time to outcome. Changes in the economic environment and farm economy during the life of the loan are significant.

The sample consists only of FSA direct loans which implies borrowers are at financial margin. Application of method to agricultural loans from conventional commercial lenders could identify different significant factors.

Using length of time to loan termination instead of just type of outcome provides for a richer analysis of loan performance. Loan performance over time is influenced by the larger economy and should be incorporated into loan performance modeling.

The study described in the paper demonstrates use of competing risks models on intermediate agricultural loans and develops how this technique can be used to learn about dynamic aspects of loan performance. Sample consists of observations on individual FSA direct loan borrowers. The FSA direct loan program is the major source of credit for agricultural borrowers at the financial margin.

The purpose of this paper is to provide a description of the “competing commitments model”.

The paper explores the “competing commitments model”.

The paper discovers that the competing commitment is a three‐stage process that is guided by: a set of questions that are designed to uncover the competing commitments; a process for determining the underlying assumptions at their core; and beginning the process of behavioural change. The “competing commitments model” is particularly useful in understanding conflicts in the diverse environment of digital library projects by providing the team members with a way to share (and work through) big assumptions that may fundamentally differ in any number of ways.

Exploring competing commitments is a positive approach for project team conflict resolution because it is not designed to identify “bad behavior” nor does it take a prescriptive approach in trying to fix behavior.

This study updates the literature review of Jones (1987) published in this journal. The study pays particular attention to two important themes that have shaped the field over the past 35 years: (1) the development of a range of innovative new statistical learning methods, particularly advanced machine learning methods such as stochastic gradient boosting, adaptive boosting, random forests and deep learning, and (2) the emergence of a wide variety of bankruptcy predictor variables extending beyond traditional financial ratios, including market-based variables, earnings management proxies, auditor going concern opinions (GCOs) and corporate governance attributes. Several directions for future research are discussed.

This study provides a systematic review of the corporate failure literature over the past 35 years with a particular focus on the emergence of new statistical learning methodologies and predictor variables. This synthesis of the literature evaluates the strength and limitations of different modelling approaches under different circumstances and provides an overall evaluation the relative contribution of alternative predictor variables. The study aims to provide a transparent, reproducible and interpretable review of the literature. The literature review also takes a theme-centric rather than author-centric approach and focuses on structured themes that have dominated the literature since 1987.

There are several major findings of this study. First, advanced machine learning methods appear to have the most promise for future firm failure research. Not only do these methods predict significantly better than conventional models, but they also possess many appealing statistical properties. Second, there are now a much wider range of variables being used to model and predict firm failure. However, the literature needs to be interpreted with some caution given the many mixed findings. Finally, there are still a number of unresolved methodological issues arising from the Jones (1987) study that still requiring research attention.

The study explains the connections and derivations between a wide range of firm failure models, from simpler linear models to advanced machine learning methods such as gradient boosting, random forests, adaptive boosting and deep learning. The paper highlights the most promising models for future research, particularly in terms of their predictive power, underlying statistical properties and issues of practical implementation. The study also draws together an extensive literature on alternative predictor variables and provides insights into the role and behaviour of alternative predictor variables in firm failure research.

This paper aims to identify and test four competing models with the interrelationships between students’ perceived service quality, students’ satisfaction, loyalty and motivation using structural equation modeling (SEM), and to select the best model using chi-square difference (Δχ2) statistic test.

The study uses survey research design to gather data regarding attitudes of students about quality of services and their level of satisfaction, motivation and loyalty. A total of 1,439 valid questionnaires were collected from four public universities in the state of Andhra Pradesh, India, and the relationships between four variables using SEM are tested.

The structural model with direct and indirect relationships between the constructs proves as a best among the competing models. The result supported direct effect of students’ perceived service quality on students’ satisfaction and motivation; and indirect effect on students’ loyalty. Implications and research contributions are discussed and directions for further research are indicated.

The study considers the examinations of the simple bivariate relationships between service quality, satisfaction, motivation and loyalty may mask or overstate their true relationships due to omitted variable bias. Structural theory with simultaneous measurement of the direct and indirect relationships between students’ perceived service quality, satisfaction, motivation and loyalty adds a unique contribution to the existing field of knowledge, especially higher education sector.

The results of SEM show that the service quality is a key antecedent to students’ satisfaction, loyalty and motivation. Motivating students for present and future studies with better participation in the process is important to increase quality and efficiency in their output. The best services also make students loyal to the institution. The findings suggested that it would be worthwhile for university’s administration to make proper allocation of resources, to provide better educational services. It is believed that this study has a significant competence for engendering more precise applications related to quality of services, especially concerning students’ satisfaction, loyalty and motivation.

The research provides significant insights and demonstrates good understanding of students’ perceived service quality in the context of Indian universities. The changing nature and need of higher education services and increase in competitive intensity necessitates higher performance levels in the realm of Indian higher education (universities). The study identified that students’ perceived service quality is a key antecedent to students’ satisfaction, motivation and loyalty, which conveys that service quality is an important construct.

Several points are addressed based on the models identified in the study. First, there is sufficient evidence of a significant bivariate relationship between service quality, satisfaction, loyalty and motivation. Second, although service quality is an important determinant of loyalty, the exact nature of this relationship remains unresolved. Third, it is evident that very few studies have investigated multiple direct links between service quality, satisfaction, motivation and loyalty. Further, there is no reported investigation of whether any or all of these variables directly and indirectly influence loyalty when the effects of service quality, satisfaction, motivation are simultaneously considered in Indian higher education sector. Therefore, to present a more pragmatic picture of these relationships, the study identified the “collective model” that investigates the underlying relationships that exist among these constructs.

This paper attempts to develop and validate a service quality instrument called HiEduQual to measure the perceived service quality of students in higher education institutions. This paper aims to propose a structural model by examining the theoretical and empirical evidences on the relationships between students’ perceived service quality (SPSQ), students’ satisfaction (SSt), students’ loyalty (SL) and students’ motivation (SM).

The paper uses survey research design to gather data regarding attitudes of students about quality of service, satisfaction, motivation and loyalty from seven public universities in India and tests the relationships between these variables using structural equation modeling.

The paper identifies a model with six-structured dimensions containing 23 items for HiEduQual. It proved the direct positive effect of the perceived service quality of students on satisfaction, loyalty and motivation. The paper also supports the partial and complete mediation role of students’ satisfaction between perceived service quality of students, their loyalty and motivation toward services being provided by the universities. The competing Model 1 (M1) with partial mediation role of students’ satisfaction between students’ perceived service quality, loyalty and motivation was proved as the best among the alternative models.

The paper developed and tested a new measurement instrument that covers all the service aspects experienced by the student as primary customer in higher education. Further studies can also measure service quality of the universities in the perspective of other key stakeholders. The authors would recommend studying other possible antecedents which would have influence on satisfaction motivation and loyalty.

The findings suggested that it would be worthwhile for university leaders to make proper allocation of resources, to provide better educational services including support services and facilities. It is believed that this paper has a significant competence for engendering more precise applications related to quality of services, especially concerning students’ satisfaction, loyalty and motivation.

The changing nature and need of higher education services and increase in competitive intensity necessitates higher performance levels in the Indian higher education (universities). These can only be achieved through a better understanding of the expectations of students and the importance placed by them on aspects such as teaching, administrative services, academic facilities, campus infrastructure, support services and internationalization. The paper identified that student perceived service quality is a key antecedent to student satisfaction, motivation and loyalty, which conveys that service quality is an important construct.

Previous studies have primarily focused on the relationship between service quality, satisfaction and loyalty. Along with the above, this paper includes students’ motivation and assesses the effect of service quality and satisfaction on motivation which was not previously used in services marketing research, especially in higher education sector. Higher education service holds some unique features like customers’ (student) cognitive participation in the service process, requirements of the students to be fulfilled by different parties and long-term continuous services. All these features require student participation. The results indicate that quality of academic and non-academic services play a vital role in motivating students to perform better in their academics.