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Purpose – Revisiting Fornell et al.'s (1996) seminal study, this chapter looks at the evidence for observed and unobserved heterogeneity within data underlying the American customer satisfaction index (ACSI) model. Examining data for two specific industries (utilities and hotels) reveals only modest differences. However, we suppose that unobserved heterogeneity critically affects the results. These insights provide the basis for shaping further differentiated ACSI model analyses and more precise interpretations.

Methodology/approach – This study applies the partial least squares (PLS) path modeling method and uses empirical data to estimate and compare the ACSI model results on the aggregate and industry-specific data levels. In addition, the finite mixture PLS path modeling (FIMIX-PLS) method is employed to further examine across industry similarities and within industry differences.

Findings – This research uncovers unobserved heterogeneity that guides forming three segments of customers within each industry. The major segment in each industry represents customers that are fairly loyal (i.e., neither disloyal nor extremely loyal) while the other two smaller segments are not as similar across the two industries. Our study identifies substantial differences across these segments within each industry. An importance-performance map analysis illustrates these differences and provides the basis for managerial implications.

Originality/value of the chapter – The unobserved heterogeneity revealed within industries in a given country (i.e., the United States of America) underlines the need to be open to differences within populations, beyond the observed heterogeneity across distinct groups or cultures, and the need to reconsider reporting requirements in academic research.

This chapter proposes a simple procedure to estimate average derivatives in nonparametric regression models with incomplete responses. The method consists of replacing the responses with an appropriately weighted version and then use local polynomial estimation for the average derivatives. The resulting estimator is shown to be asymptotically normal, and an estimator of its asymptotic variance–covariance matrix is also shown to be consistent. Monte Carlo experiments show that the proposed estimator has desirable finite sample properties.

The study explored various dimensions of overconfidence bias (OB) among retail investors in Indian financial markets. Further, these dimensions were validated through formative assessments for OB.

The study applied exploratory factor analysis (EFA) to 764 respondents to explore dimensions of OB. These were validated with formative assessments on 489 respondents by the partial least square path modeling (PLS-PM) approach in SmartPLS 4.0 software.

The major findings of EFA explored four dimensions for OB, i.e. accuracy, perceived control, positive illusions and past investment success. The formative assessments revealed that positive illusions followed by past investment success among retail investors played an instrumental role in orchestrating the OBs that affect investment decisions in financial markets.

The formative index of OB has several practical implications for registered financial and investment advisors, bank advisors, business media companies and portfolio managers, besides individual investors in the domain of behavioral finance.

This research provides a novel approach to provide a formative index of OB with four dimensions. This formative index can acts as an overview for upcoming researchers to investigate the OB of retail individual investors.

1. Overconfidence bias is an important predictor of retail investors' behavior

2. Formative dimensions of the overconfidence bias index.

3. Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

4. Modern portfolio theory and illusion of control theory support this study.

Overconfidence bias is an important predictor of retail investors' behavior

Formative dimensions of the overconfidence bias index.

Accuracy, perceived control, positive illusions and past investment success are important dimensions of overconfidence bias.

Modern portfolio theory and illusion of control theory support this study.

The purpose of this paper is to examine the influence of perceived organizational support (POS), psychological empowerment (PE) and leader member exchange (LMX) as antecedents on the commitment level of employees working in the hotel industry and their subsequent impact on service quality (SQ).

Data were collected from 436 employees and 1,320 customers from 34 hotels with the help of a structured self-administered questionnaire. The analysis of data were done by applying a confirmatory factor analysis along with a structural equation model.

The findings of the study indicate that organizational commitment acts as a full mediator between: POS and SQ; and leader-member exchange and SQ. On the other hand, it acts a partial mediator between PE and SQ.

This study contributes to organizational behavior and services marketing literature. It examines the relationship between antecedents (LMX, PE and POS) and outcome (SQ) so as to observe the cumulative effect of antecedents on outcome through an integrated model. The study suggests the managerial as well as theoretical implications on the basis of the findings.

The purpose of this study is to quantitatively examine the impact of perceived supervisor support, person-job fit (PJF) and person-organization fit (POF) on the company’s value through job satisfaction (JS).

Data were collected from 220 respondents selected from different organizations in India using standard questionnaires. To estimate the hypothesized model fit indices, partial least square structural equation modeling were used.

Findings suggest that there is a significant relationship among supervisor support, PJF and POF with JS and perceives company value.

Human resource (HR) professionals need to understand how they can help to increase the JS of employees before they decide on HR measures that would help improve the perceived contribution to company value.

Support from the superior induces a sense of value and worthiness to the employee, which, in turn, strengthens the relationship between the employees with his/her organization. Along with this PJF and POF are other significant factors for employee satisfaction. If the person likes the job or in other words if the prescribed job is suitable for the person, then the employee feels significant, which amplifies JS. The same is applicable for the POF. Consequently, the perceived contribution to company value increases.

Since the past two years, workplace dynamics has changed, as employees have witnessed uncertainty and a constantly fluctuating business environment due to COVID-19. The outbreak is nearly over, but it has led to new work settings in most parts of the world. This requires a suitable leadership approach to derive strategic decisions and cultivate proficiency amongst employees in the new work setting. The purpose of the article is to explore the effects of ambidextrous leadership (AL) in boosting social capital (SC) which further lead to employee creative work behavior. Further, the study also examined the moderating role of well-being in enriching creative work behavior.

In this study, 281 knowledge workers working in Mumbai were selected as subjects for the study. Structural equation modelling using analysis of moment structure was used to test the mediation. Later, moderated regression analysis confirmed the moderating role of well-being in employee creative behaviour.

The results confirmed the role of AL comprising closed and open leadership behaviours in enhancing the SC, which is an important element to cultivate creative behaviour amongst employees. In addition, the role of well-being is found to be critical for enhancing creative work behaviour.

The study will help organizations to understand the role of AL, SC and well-being in enhancing creative behaviour amongst knowledge workers.

This study contributes to leadership literature by attempting to integrate the concepts of leadership with SC, well-being and creative work behaviour, which has rarely been done in the Indian context.

The purpose of this paper is to examine the prevalence of stress among police officers and the impact of it on their health.

A survey was conducted in randomly selected four cities from the state of Uttarakhand, India. A total of 444 police officers below the inspector-level ranks from eight police stations participated in this study. Structural equation modeling was used to examine the inter-relationship between the factors affecting health and assessing the mediating role of stress.

Findings revealed that organization politics and work overload held a positive relationship whereas perceived organization support had an inverse relation with stress. Work overload was found to be the highest contributor in causing stress with a strong positive relationship value of 0.52 with stress. Further, stress had a strong impact on the health of the police officers, indicated by the direct relation with a value of 0.55.

The study is limited to the geographical area of Uttarakhand. Findings revealed that the health of the policemen was highly affected by the stressful work environment and work overload. Hence, higher authorities of the police department are required to pay attention on the welfare activities of the force to improve the prevailing situation.

This study would be contributing to the literature available in Indian context by discussing the various antecedents of stress among the police officers.

The purpose of this paper is to investigate the mediating role of self-esteem in the relationship between parent-adolescent relationship and adolescent compulsive buying behaviour. Using a sample of 300 adolescents (15-18 years) in India and the structural equation modelling technique, the findings reveal that self-esteem mediates the relationship between parent-adolescent relationship and adolescent compulsive buying behaviour.

The present study is the first to experimentally manipulate important parent-adolescent relationship and measures its impact on compulsive buying among a sample of 15-18-year old adolescents. Next, the authors investigate the mediating role of self-esteem for the above relationship. Confirmatory factor analysis and structural equation modelling have been used in the study.

The study also establishes that familial conflict and cohesion acts as major sources of adolescent compulsivity. The authors have also examined the mediating role of self-esteem on the above relationships and found that adolescents’ compulsivity varies with the level of self-esteem (i.e. higher level of self-esteem leads to lower levels of adolescents’ compulsivity). The practical and theoretical implications are discussed within the context of adolescents’ compulsivity.

The study makes some inimitable and significant contributions to the literature. It portrays one of few studies to investigate compulsive buying during adolescence period – a hard to reach population. Here authors experimentally manipulate parent-adolescent relationship to investigate its impact on compulsive buying. The study’s findings in regard to mediating effect of self-esteem on the parent-adolescent relationship and adolescents’ compulsive buying behaviour suggest that compulsive buying begins during adolescence period and is a common coping strategy for both boys and girls.

To maintain the bottom line of food import risk in China, this paper proposes a novel risk state evaluation model based on bottom-line thinking after analyzing the decision-making ideas embedded in the bottom-line thinking method.

First, the order relation analysis method (G1 method) and Laplacian score (LS) are applied to calculate the constant weights of indexes. Then, the worst-case scenario of food import risk can be estimated to strive for the best result, so the penalty state variable weight function is introduced to obtain variable weights of indexes. Finally, the study measures the risk state of China's food import from the overall situation using the set pair analysis (SPA) method and identifies the key factors affecting food import risk.

The risk states of food supply in eight countries are in the state of average potential and partial back potential as a whole. The results indicate that China's food import risks are at medium and upper-medium risk levels in most years, fluctuating slightly from 2010 to 2020. In addition, some factors are diagnosed as the primary control objects for holding the bottom line of food import risk in China, including food output level, food export capacity, bilateral relationship and political risk.

This paper proposes a novel risk state evaluation model following bottom-line thinking for food import risk in China. Besides, SPA is first applied to the risk evaluation of food import, expanding the application field of the SPA method.

This study aims to examine the role of an overall model fit assessment in the context of partial least squares path modeling (PLS-PM). In doing so, it will explain when it is important to assess the overall model fit and provides ways of assessing the fit of composite models. Moreover, it will resolve major concerns about model fit assessment that have been raised in the literature on PLS-PM.

This paper explains when and how to assess the fit of PLS path models. Furthermore, it discusses the concerns raised in the PLS-PM literature about the overall model fit assessment and provides concise guidelines on assessing the overall fit of composite models.

This study explains that the model fit assessment is as important for composite models as it is for common factor models. To assess the overall fit of composite models, researchers can use a statistical test and several fit indices known through structural equation modeling (SEM) with latent variables.

Researchers who use PLS-PM to assess composite models that aim to understand the mechanism of an underlying population and draw statistical inferences should take the concept of the overall model fit seriously.

To facilitate the overall fit assessment of composite models, this study presents a two-step procedure adopted from the literature on SEM with latent variables.

This paper clarifies that the necessity to assess model fit is not a question of which estimator will be used (PLS-PM, maximum likelihood, etc). but of the purpose of statistical modeling. Whereas, the model fit assessment is paramount in explanatory modeling, it is not imperative in predictive modeling.