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This study aims to explore the influence of creative tourist experiences (CTE) on tourists’ recommendation intentions (RCI) toward creative tourist destinations. This study examines the roles of tourist engagement and satisfaction in this relationship, proposing a sequential mediation model based on the cognitive-affective-conative model.

The research surveyed travelers to Kinnaur, Himachal Pradesh, India, using a structured questionnaire. Through purposive sampling data were collected from 413 generation Z (Gen Z in short) tourists. The study used exploratory factor analysis, confirmatory factor analysis and sequential mediation analysis. The present research used Model 6 by Andrew Hayes in the SPSS process macro to test the serial mediation.

The findings emphasize the importance of active engagement in creative tourism and its potential to transform cultural heritage into enriching experiences, thereby influencing tourists’ recommendation behaviors. Results of sequential mediation analysis show that there is a significant and positive impact of CTE on tourist’s RCI. Further, results showed the sequential mediation effect of tourist engagement and satisfaction on the relationship between CTE and RCI.

The findings offer valuable insights for destination managers and policymakers in creative tourism. Enhancing tourist engagement and satisfaction through creative experiences can effectively increase RCI, contributing to the sustainable management of cultural resources and preventing the over-commercialization of cultural heritage.

This research contributes to the literature on creative tourism by empirically testing the sequential mediation model and highlighting the pivotal role of tourist engagement and satisfaction in transforming creative experiences into positive behavioral outcomes. This study provides a nuanced understanding of the factors influencing tourists’ RCI in creative tourism contexts.

The present study examines the fluctuations in Socioeconomic and demographic (SED) factors and the prevalence of Non-Communicable Diseases (NCDs) across clusters of states in India. Further, it attempts to analyze the extent to which the SED determinants can serve as predictive indicators for the prevalence of NCDs.

The study uses three rounds of unit-level National Sample Survey self-reported morbidity data for the analysis. A machine learning model was constructed to predict the prevalence of NCDs based on SED characteristics. In addition, probit regression was adopted to identify the relevant SED variables across the cluster of states that significantly impact disease prevalence.

Overall, the study finds that the disease prevalence can be reasonably predicted with a given set of SED characteristics. Also, it highlights age as the most important factor across a cluster of states in understanding the distribution of disease prevalence, followed by income, education, and marital status. Understanding these variations is essential for policymakers and public health officials to develop targeted strategies that address each state’s unique challenges and opportunities.

The study complements the existing literature on the interplay of SEDs with the prevalence of NCDs across diverse state-level dynamics. Its predictive analysis of NCD distribution through SED factors adds valuable depth to our understanding, making a notable contribution to the field.

The purpose of this study is to identify the prominent research constituents in the domain of integration of Lean manufacturing and Industry 4.0 techniques and analyze the intellectual structure among them.

A bibliometric analysis of articles based on Donthu et al. (2021a) has been adopted to conduct a systematic review of the integration of Lean manufacturing and Industry 4.0 using the Scopus database.

The co-citation analysis and bibliographic coupling depicted three clusters and themes around which the research related to the integration of Lean manufacturing and Industry 4.0. Publications related to the topic have majorly focused on the development of conceptual models and frameworks for integrating Lean manufacturing and Industry 4.0, analyzing the compatibility between the two techniques for better implementation of one another and the techniques' combined impact on operational performance.

Most of the review studies related to the domain of integration of Lean manufacturing and Industry 4.0 have adopted a systematic literature review methodology. The present study has tried to infer the intellectual framework of the research being conducted in the said domain using the bibliometric analysis to identify the prominent research constituents in the field and examine the intellectual relationship between them.

This study aims to propose a conceptual model that examines the role of ethical climate on work–family enrichment in the restaurant industry, which is one of the most vulnerable sectors affected by global crises such as the COVID-19 pandemic. The mediating effects of psychological attachment and psychological capital and the moderating effects of job autonomy were also investigated to enrich understanding of ethical climate and work–family enrichment.

The conceptual model was evaluated by using a quantitative–qualitative mixed-methods approach. In Study 1, survey data was collected from a sample of 405 restaurant frontline employees and analyzed using partial least squares structural equation modeling. In Study 2, interviews were conducted with eight restaurant frontline employees and analyzed thematically. The data for Study 1 and Study 2 was collected from Jharkhand, a state in eastern India.

The results of Study 1 show a direct relationship between ethical climate and work–family enrichment. The mediating effect of psychological attachment and psychological capital on that direct relationship was also established, whereas job autonomy was found to be a significant moderator that negatively affects psychological attachment and work–family enrichment. The qualitative insights in Study 2 shed additional light on the rationales of the effects observed in Study 1 through the voices of restaurant frontline employees whilst triangulating the quantitative findings in Study 1.

This research contributes novel insights that explain how ethical climate positively shapes work–family enrichment through the lens of psychological attachment and psychological capital, albeit cautiously, given the negative effect of job autonomy. Nevertheless, this research remains limited to restaurant frontline employees, thereby necessitating future research in other service industries to improve the generalizability of its findings.

This research offers a seminal extension of the direct effect of ethical climate on work–family enrichment (i.e. the “what”) by theorizing and validating the mediating (i.e. the “why”) and moderating (i.e. the “how”) effects of psychological attachment, psychological capital and job autonomy.

The primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).

Initially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.

The ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.

Taking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.

This study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.

For the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

The purpose of this paper is to discuss the implementation of lean methodology to reduce the turnaround time (TAT) of a clinical laboratory in a super speciality hospital. Delays in report delivery lead to delayed diagnosis increased waiting time and decreased customer satisfaction. The reduction in TAT will lead to increased patient satisfaction, quality of care, employee satisfaction and ultimately the hospital’s revenue.

The generic causes resulting in increasing TAT of clinical laboratories were identified using lean tools and techniques such as value stream mapping (VSM), Gemba, Pareto Analysis and Root Cause Analysis. VSM was used as a tool to analyze the current state of the process and further VSM was used to design the future state with suggestions for process improvements.

This study identified 12 major non-value added factors for the hematology laboratory and 5 major non-value added factors for the biochemistry lab which were acting as bottlenecks resulting in limiting throughput. A four-month research study by the authors together with hospital quality department and laboratory staff members led to reduction of the average TAT from 180 to 95minutes in the hematology lab and from 268 to 208 minutes in the biochemistry lab.

Very few improvement initiatives in Indian healthcare are based on industrial engineering tools and techniques, which might be due to a lack of interaction between healthcare and engineering. The study provides a positive outcome in terms of improving the efficiency of services in hospitals and identifies a scope for lean in the Indian healthcare sector.

Applying lean in the Indian healthcare sector gives its own potential solution to the problem caused, due to a wide gap between lean accessibility and lean implementation. Lean helped in changing the mindset of an organization toward providing the highest quality of services with faster delivery at an optimal cost.

This paper is an effort to reduce the gap between healthcare and industrial engineering and enhancing the use of lean practices in Indian healthcare. The study is motivated toward implementing lean methodology successfully in services.

The objective of this research is to identify and prioritize the critical factors that influence the adoption of blockchain technology within the banking sector.

A well-known theoretical framework, the “Technology Organization Environment (TOE),” was chosen to analyze what criteria and sub-criteria affect blockchain adoption in the banking sector after a thorough assessment of the prior literature. Following that, 3 evaluation criteria and 14 sub-criteria were selected and verified using expert opinion. A survey design was created, and data for the study has been collected from various information technology (IT) managers/officers in the banking sector. A fuzzy analytic hierarchy process (Fuzzy-AHP) was then used to meet the purpose of the research.

The study identified that the organizational dimension is the most significant criteria for blockchain adoption in the banking sector, followed by the environmental dimension. In contrast, the technological dimension is the least influential criterion. Clientele pressure, IT resources, financial resources, pressure from competitors and relative advantage are the most influential sub-criteria for blockchain adoption.

This study provides valuable insights to bank managers, blockchain and IT developers, third-party service providers and policymakers. For instance, adopting the same blockchain platform is easier for both large and small banks for banking operations by using third-party service provider. At the same time, banks should have the banks' own core team to implement the blockchain-based systems or to have control over the third-party service providers during the adoption stage.

To the best of the authors' knowledge, no empirical studies have used a holistic organizational context to understand the factors influencing the adoption of blockchain technology from traditional to blockchain-based banking systems.

This study aims to examine the reaction of anchor investors (AIs) to pre-IPO earnings management (EM). The authors use the unique detailed bid data from the Indian anchor experiment. The authors also study the reputed AIs’ EM detection ability and pricing behavior in response to pre-IPO EM.

The authors use unique AI bid data for 169 Indian IPO firms. Utilizing the logistic regression and Tobit regression models with industry and year-fixed effects, the authors examine the relationship between various measures of AI participation and proxies of short-term and long-term discretionary accruals.

The authors document that pre-IPO EM is positively associated with the likelihood of anchor backing but negatively related to the likelihood of reputed anchor backing. The findings indicate that AIs are misled by pre-IPO EM, but reputed AIs are not. The authors also observe that reputed AIs, compared to the non-reputed, pay less than the upper band with increasing EM. The findings are robust to using various AI measures and EM proxies.

The findings have significant implications for regulators in the implementation of AI concept in non-anchor markets and better implementation of policies in existing anchor settings. Findings can also be relevant for non-institutional investors in the IPO domain.

This is one of the few studies on institutional investors' IPO bidding behavior in response to pre-IPO EM. However, this is the first study to analyze AIs' IPO bidding behavior in response to pre-IPO EM.

Massive open online courses (MOOCs) are among the most recent e-learning initiatives to gain widespread acceptance among universities. However, despite MOOCs' “much-documented” benefits, many questions are being raised late regarding the long-term sustainability of the open online teaching e-learning model. With high dropout rates in MOOCs courses, recent research has focused on the challenges limiting MOOCs’ growth. But most of the research is directed toward students’ perspectives, leaving the instructors’ perspective. One of the most important aspects of instructors’ perspective is the motivation for MOOCs' development and delivery.

The present study collected the data from 25 MOOC developers of Indian origin. To prioritize or rank the motivational factor behind developing a MOOC, a fuzzy-analytical hierarchical process (F-AHP) technique was applied to the data set. The primary motivational factors considered for the study were professional development, altruism, personal development, institutional development, intrigue, monetary benefits and peer influence.

The results showed that professional development and personal development are two prime motives that drive MOOCs development. Monetary benefits and peer influence were the least important factors among all the factors considered for the study.

Previous studies have identified and modeled the motivational factors that contribute toward developing MOOCs. However, there was little knowledge about the hierarchy among the motivating factors. The present study fills this gap by establishing the ranking of motivational factors responsible for MOOCs development.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0205.

Owning to the influence small retailers have on the customer’s final choice, the purpose of this paper is to investigate the factors that dominate small retailer’s assortment planning decisions. Drivers of product adoption by small retailers are the focus of study. Earlier research works have primarily focused on the profit oriented factors of retailing. It is a multidimensional approach of understanding the decision making of small retailers.

The study is an exploratory in nature, using a mixed method approach that involves both qualitative and quantitative methodology. In the first stage of the study, grounded theory has been adopted that helps in building a conceptual model, which is further validated using SEM. Rural areas of Jammu and Punjab have been targeted to collect data.

The study provides a conceptual model of product assortment planning for small retailers. The results indicate retail margin, which is the most important criterion toward product selection. Small retailers understand the customer profile and their catchment before selecting a product for their store. Store design is an important variable which impacts the number of categories kept in the store as the shelf space is limited. While determining the assortment planning for the store the retailers need to think in advance about buyer, supplier, environmental and the surplus oriented factors while determining the assortment planning for the store.

In developing economies like India, major population (customers) lie in the rural areas of the country and prefer small retailers to shop their daily necessities. The study proposed that the manufacturers need to maintain good and healthy relationship with the associates of the channel and the retailers that are in connected with the end consumer. Marketing managers of firms with target audience as small retailers can draw many inferences from the present study. They may devise rural strategies keeping attributes like localization of supplier, doorstep delivery, supply frequency, etc., on the basis of product demand and attribute.

This paper fulfills an identified need to explore the assortment planning criteria of BOP retailers in India. Also the mixed methodology is attractive and new in the retail domain.