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This study intends to investigate how an employee's proactive personality and a supervisor's idiosyncratic deals (i-deals) relate to their subordinates' affective commitment (AC) and occupational well-being (OWB), in light of the mediating role of subordinates' i-deals, using proactive motivation theory and the job demand–resource (JD-R) model as theoretical foundations.

The study consisted of 342 employees working in the hospitality industry. To examine the proposed model, the researchers used the structural equation modelling approach and bootstrapping method in AMOS.

The results affirmed the influence of subordinates' proactiveness on AC and OWB, but no direct influence of supervisors' prior i-deals on subordinates' AC and OWB was established. When investigating the mediational role of subordinates' i-deals, a partial mediation effect was found between subordinates' proactive personality with AC and OWB, whereas full mediation was established between supervisors' i-deals and subordinates' AC and OWB.

These findings shed light on how i-deals improve AC and OWB for both groups of supervisors and subordinates. In an era of increasing competition amongst organizations operating within the hospitality industry, i-deals serve as a human resource strategy to recruit, develop and retain talented individuals.

The novelty of this research lies in its specific investigation of the combined influence of proactive personality as an individual factor and supervisors' i-deals as an organizational factor on subordinates' i-deals within the context of the hospitality industry. Furthermore, it aims to analyse the potential impact of these factors on AC and OWB.

Block chain technology (BCT) has apparent capability of handling information in digital format, which has dragged attention of the practitioners for its utility in industrial and manufacturing practices. Conversely, the managerial adoption of BCT is relatively limited, which motivated the authors to identify crucial dimensions that can persuade the acceptance of BCT from an executive perspective. Thus, the present study is aimed to conduct to understand crucial barriers under BCT for managerial implementation in supply chain management (SCM) of small and medium enterprises (SMEs).

The present study investigated evident barriers to understand implementation of BCT. A questionnaire based survey is performed to collect primary data from service and manufacturing based companies in India. Survey responses are received online and the data is analyzed in a scorecard. The scorecard embedded the scribed entries of Likert scale to determine the relative score.

In present study, sixteen barriers from three categories named as technological, organizational and environmental are evaluated, where, five sub-barriers from technological domain, seven sub-barriers from organizational domain and four sub-barriers from environmental domain are evaluated. The findings of the study determined that the three factors, i.e. “complexity in setup/use”, “Security and privacy concern” and “Technological awareness” mostly affect the adaptation of BCT in SCM. Conversely, “Market dynamics”, “Scalability” and “Cost” do not influence the intention to adopt the technology.

Only few studies have endeavored to ascertain the BCT adoption in SCM of SMEs in developing country like India. Thus, the study is filling a momentous gap of mapping BCT dimensions in the scholastic literature. The findings are expected to enable SMEs to understand important factors to be considered for adopting BCT in their curriculum. Furthermore, the study may benefit the BCT developers and suppliers to endure customized solutions based on the findings.

The objective of the study is to develop a methodology to strategically rank store locations using criteria such as population, store site characteristics, economic considerations, competition and so on to select the most optimal retail convenience store location.

A case of National Capital Region, India, for a 24-h convenience store was considered for the study and the major criteria that affect the performance of a convenience store are identified, such as population characteristics, economic criteria, competition, consumer accessibility, store size, total cost, site attractiveness and security. Fuzzy AHP is utilized to find the weightage for each criteria and a combination of fuzzy TOPSIS and grey relational analysis (GRA) is applied to rank the alternative using these criteria weight. Further, results obtained are compared with results from fuzzy TOPSIS and fuzzy VIKOR methods. Sensitivity analysis is also performed for ensuring the robustness of the framework.

It is observed that outcomes do not change under various settling coefficient values, demonstrating that the methodology is very robust. The developed framework will be quite useful to diverse retailers looking to expand and generate substantial profits.

A large sample size of number of locations encourages generalization of results. Strategic ranking of the selected locations is carried out on a few selected criteria. The study was limited by the designated geographical area.

The study contributes to the few available articles on convenience store selection using combination of fuzzy AHP, fuzzy TOPSIS and GRA for a developing country.