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This study examines how intellectual capital (IC) drives firm performance via the lens of dynamic capabilities (DCs). Drawing on resource-based view (RBV) and dynamic capability view (DCV), the authors elaborate the mediating role of learning, integration and reconfiguration DC in the Indian banking context.

A sample of 358 top- and middle-level managers from the Indian banking sector was administered with structured questionnaires for data collection. Structural equation modeling (SEM) and Sobel test were used to analyze the data and test the hypothesized mediating effect.

The findings reveal that learning and integration DCs are key mediators in IC and banks' performance relationships in an emerging economy context. In contrast, the analysis revealed partial mediating role of reconfiguration DC. Furthermore, the learning DC has been identified as the primary mediating mechanism for transforming bank's IC into performance benefits.

This study provides an important implication for the IC and DC link by empirically developing and validating a model in the Indian banking sector and making a several contributions to the related literature. This sector needs to incorporate and strengthen their IC and DCs to attain enhanced performance in today's dynamic environment. Bank managers can use these findings to bring their knowledge-related activities to channelize specific DCs to transform banks' IC when seeking to improve overall performance. Theoretically, this study extends previous research by outlining a set of organizational elements that tend to influence firm performances with the help of IC, learning, integration and reconfigurations DCs.

Although several studies have investigated the links between IC, DC and firm performance, studies on emerging economies are scarce. This study is one of the most in-depth investigations of the relationship between IC, learning, integration and reconfiguration DCs and firm performance in an integrated framework, with a particular focus on the banking sector of an emerging economy.

This research examines and analyzes the impact of employee branding and employer branding in multinationals that exceeded the national boundaries in globalization. The motive of the research is to identify the significance of employer and employee branding for the success of the multinationals. The emergence of a MNC culture in India is widespread, and it promotes an employee-oriented philosophy by making all the amenities available to the employees. Multinational organizations focus on employee and employer branding to achieve the desired goals. Employee branding is a new term in the service industry that emphasizes the internal marketing of the organization Infront towards the external image of a company. India has a significant presence of service sectors as in the top 10 around the world. Employment rate in the service sector in India is more that 32.33% as per the collected data by the World Bank in 2020, wherein the large number of employees contributing their services in the different fields becomes a matter of concern for a company’s policies. This research was conducted on a population sample size of 204 respondents working in multinational organizations of Gurugram, India, using convenience sampling through a structured questionnaire. Data analysis of the survey was coded in Ms-excel 2015 and SPSS-21. Primary and secondary data are used in this study. Primary data are collected through questionnaire method, and secondary data are collected through journals, books, websites etc. This study will help human resource managers to improve HR policies and organization culture and to increase employee branding to gain desired success in organizations.

The successive waves of the Covid-19 SARS-II pandemic and the attendant lockdown imposed by the governments worldwide drove the economic activities to a halt. Offices and factories closed, production of goods and services declined and supply chains got severely disrupted. Many companies were embattled with the grim reality of shrinkage of aggregate demand, first due to supply shock and later due to loss of jobs and wages. Amidst all this, the handling and shipping of commodities became extremely complex. As the pandemic shifted consumer preference in favour of digital platforms, more and more fast-moving consumer goods (FMCG) companies were confronted with multiple strategies and choices of an appropriate distribution channel to ensure smooth delivery of raw materials and products. The present study aims to study this shift and its implications in the Indian context.

A mix-method approach, integrating quantitative and qualitative analysis, is employed to investigate the factors influencing the selection of distribution channels amongst general trade, modern trade, e-commerce and hyperlocal for FMCG companies in India. The first phase of the study uses exploratory factor analysis (EFA), followed by the application of analytical hierarchy process (AHP) approach in a fuzzy environment to realise the priority weights and ranking of the identified factors. Finally, sensitivity analysis is performed to confirm the robustness of the fuzzy analytical hierarchy process (FAHP) outcomes.

The study revealed that modern trade has emerged as the most favoured channel in the post-pandemic Indian economy. It has the potential to disrupt general trade. The study also revealed that the hyperlocal delivery model is not economically viable, and the partnership of FMCG companies with these applications is at best a short-term solution. However, it must be submitted that due to its sheer capability to ensure quick deliveries within a confined geographic area, hyperlocal delivery will gain momentum with the advancement of technology.

This study can be seen as the first attempt to investigate the issues related to the selection of the distribution channels in the FMCG sector of India using multi-criteria decision-making technique (MCDM).

The purpose of the study is to identify the key antecedents relating to the interaction design of the e-groceryretail mobile applications and offer innovative marketing interventions to facilitate consumer–brand interaction and generate continuous usage intention.

Data were collected from the subjects using a personally administered questionnaire by adopting a non-probability method. The target respondents of this study were individuals who are users of smartphone and have purchased groceries through mobile applications at least once in two months. On the basis of responses received, a sequential predictive analytic method that includes structural equation modelling (SEM) and artificial neural network (ANN) techniques were employed.

The findings of the study highlighted the critical role of collaboration design in harbouring satisfaction and maintaining a regular clientele for e-grocery applications by confirming the presence of complementary mediation. Such validated proposition and tested research model backed by significant methodological rigour advances the research based on post-acceptance behavioural affordances in interactive marketing literature.

The study endeavours to understand users' post-acceptance behaviour by analysing the contemporary factors relating to the interaction design of the platform in terms of mobile application attributes that would drive user patronage intentions. Further, the study highlights the pioneering role of collaboration design for e-grocery retailers, as the recent alliances among strategic players to achieve synergistic business leadership have proven to be a game-changing evolution in the industry.

Achieving a zero-carbon city requires a long-term strategic perspective. The authors propose a decision-making model which would take into account the economic, environmental and social impacts for prioritizing the zero-carbon measures for sustainable urban transportation.

An integrated intuitionistic fuzzy gained and lost dominance score (IF-GLDS) model is introduced based on intuitionistic fuzzy Yager weighted aggregation (IFYWA) operators and proposed weight-determining IF-SPC procedure. In addition, a weighting tool is presented to obtain the weights of decision experts. Further, the feasibility and efficacy of developed IF-SPC-GLDS model is implemented on a multi-criteria investment company selection problem under IFS context.

The results of the developed model, “introducing zero-emission zones” should be considered as the first measure to implement. The preference of this initiative offers sustainable transport in India to achieve a zero-carbon transport by having the greatest impact on the modal shift from cars to sustainable mobility modes with a lower operational and implementation cost as well as having greater public support. The developed model utilized can be relocated to other smart cities which aim to achieve a zero-carbon transport. Sensitivity and comparative analyses are discussed to reveal the robustness of obtained result. The outcomes show the feasibility of the developed methodology which yields second company as the suitable choice, when compared to and validated using the other MCDA methods from the literature, including TOPSIS, COPRAS, WASPAS and CoCoSo with intuitionistic fuzzy information.

A new intuitionistic fuzzy symmetry point of criterion (IF-SPC) approach is presented to find weights of criteria under IFSs setting. Then, an IF-GLDS model is introduced using IFYWA operators to rank the options in the realistic multi-criteria decision analysis (MCDA) procedure. For this purpose, the IFYWA operators and their properties are developed to combine the IFNs. These operators can offer a flexible way to deal with the realistic MCDA problems with IFS context.

Reverse logistics (RL) is a type of supply chain management that moves goods from the end customer to the original manufacturer for reuse, remanufacturing and disposal purposes. Owing to growing environmental legislations and the development of new technologies in marketing, RL has attracted more significance among experts and academicians. Outsourcing RL practices to third-party reverse logistics provider (3PRLP) has been identified as one of the most important management strategies due to complexity of RL operations and the lack of available resource. Current sustainability trends have made 3PRLP assessment and selection process more complex. In order to select the 3PRLP, the existence of several aspects of sustainability motivates the experts to establish a new multi-criteria decision analysis (MCDA) approach.

With the growing complexity and high uncertainty of decision environments, the preference values of 3PRLPs are not always expressed with real numbers. As the generalized version of fuzzy set, intuitionistic fuzzy set and Fermatean fuzzy set, the theory of q-rung orthopair fuzzy set (q-ROFS) is used to permit decision experts (DEs) to their assessments in a larger space and to better cope with uncertain information. Given that the combined compromise solution (CoCoSo) is an innovative MCDA approach with higher degree of stability and reliability than several existing methods.

To exhibit the potentiality and applicability of the presented framework, a case study of S3PRLPs assessment is taken from q-rung orthopair fuzzy perspective. The assessment process consists of three sustainability aspects namely economic, environment and social dimensions related with a total of 14 criteria. Further, sensitivity and comparative analyses are made to display the solidity and strength of the presented approach. The results of this study approve that the presented methodology is more stable and efficient in comparison with other methods.

Thus, the objective of the study is to develop a hybrid decision-making methodology by combining CoCoSo method and discrimination measure with q-ROFS for selecting an appropriate sustainable 3PRLP (S3PRLP) candidate under uncertain environment. In the proposed method, a novel procedure is proposed to obtain the weights of DEs within q-ROFS context. To calculate the criteria weights, a new formula is presented based on discrimination measure, which provides more realistic weights. In this respect, a new discrimination measure is proposed for q-ROFSs.

The study intends to examine the generational differences between GenY and GenZ Indian generational cohorts on the study variables, i.e. core self-evaluations (CSE), team cohesion, organizational culture and team performance. Further, the present research aims to analyze the impact of CSE, team cohesion and organizational culture on team performance as antecedents.

The study has adopted a descriptive cross-sectional survey method where the data were collected from Indian working professionals who belonged to GenY and GenZ generational cohorts. Further, a total of 370 responses were received, and thereafter, the data were analyzed by employing significant statistical tests such as exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation modeling (SEM) and an independent samples t-test.

The study results revealed that GenY and GenZ cohorts significantly differ on CSE, team cohesion and organizational culture. However, no significant difference was reported in team performance between these two generational cohorts. Also, the study results disclosed that CSE, team cohesion and organizational culture positively influence team performance by acting as its determinants.

The study reports differences between GenY and GenZ that would assist managers in effectively dealing with these generational cohorts and formulating human resource (HR) policies that can accommodate the needs of these two cohorts. Additionally, the study benefits managers by highlighting the importance of core-self evaluations, team cohesion and organizational culture to enhance team performance.

Existing research depicts that there lies a paucity of generational studies in the Indian context. The present study attempts to address this lacuna by putting pioneering efforts into this field. The main contribution of the study lies in empirically investigating the Indian generational cohorts (GenY and GenZ) in the organizations. Further, the study has also conceptualized and examined a team performance model by considering factors at three levels (individual, team and organization).

The study aims to define the term “generation” by proposing an integrated design based on age-period-cohort effects and by proposing an Indian generational cohort framework categorizing Indian generational cohorts into four categories, namely, Baby Boomers, GenX, GenY, and GenZ. The study further aimed to capture the existing generational differences between GenY and GenZ cohorts in the Indian teams on team climate, transactive memory system, and team leader humility.

For the first two objectives a literature review methodology along with the author's proposition was adopted. An integrated design was proposed by reviewing the relevant sociological literature to define generations. Thereafter, an Indian cohort framework was proposed categorizing them into four groups Baby Boomers, GenX, GenY, and GenZ. Following that, for the last objective, i.e. to identify the differences between cohorts, empirical data were collected by a structured questionnaire that was disseminated to GenY and GenZ Indian working professionals. A total of 229 responses were used for observing the differences or similarities between GenY and GenZ cohorts on the study variables by employing an independent samples t-test.

The study proposed an integrated design (age, period, and cohort effect). Following that, an Indian generational cohort's framework has been outlined categorizing Indian cohorts based on their birth years, age groups, developmental stages, formative years, major Indian historical events, and various characteristics possessed by them. Moreover, the empirical findings support the existing generational disparities and depict that GenZ holds a higher inclination towards transactive memory systems and team climate whereas GenY holds more inclination toward leader humility.

The study put forth its contribution to research scholars by categorizing Indian generational cohorts in a rationalized manner based on an integrated design (age-period-cohort) effect. The study would further assist concerned authorities and managers in formulating HR policies to deal with the underlying generational differences highlighted by the study.

As there lies a paucity of generational frameworks in the Indian context, this study is the first attempt in this direction which categorizes Indian generational cohorts based on a unique integrated design including age-period-cohort effects. In addition, the study also investigated these cohorts in Indian organizations to observe the existing variations.

The concept of ubiquitous assimilation in e-commerce, denoting the seamless integration of technologies into customer shopping experiences, has played a pivotal role in aiding e-satisfaction and, consequently, fostering patronage intention. Among these, text-based chatbots are significant innovations. In light of this, the paper aims to develop a conceptual framework and comprehend the patronage behaviour of artificial intelligence-enabled chatbot users by using chatbot usability cues and to determine whether the social presence and flow theories impact e-satisfaction, which leads to users’ patronage intention. The current research provides insights into online travel agencies (OTAs), a crucial segment within the travel and tourism sector. Given the significance of building a loyal clientele and cultivating patronage in this industry, these insights are of paramount importance for achieving sustained profitability and growth.

The research framework primarily focused on the factors that precede e-satisfaction and patronage intention among chatbot users, which include social presence, flow, perceived anthropomorphism and need for human interaction. The researchers collected the data by surveying 397 OTA chatbot users by using an online questionnaire. The data of this cross-sectional study were analysed using covariance-based structural equation modelling.

Findings reveal that e-satisfaction is positively linked with patronage intention and the variables of social presence and flow impact e-satisfaction along with chatbot usability cues. There were direct and indirect relations between chatbot usability and e-satisfaction. Moreover, the personal attributes, “need for human interaction” and, “perceived anthropomorphism” were found to moderate relations between chatbot usability cues, social presence and flow.

The impact of chatbot’s usability cues/attributes on e-satisfaction, along with perceived attributes – social presence and flow in the realm of OTAs contributes to the human–chatbot interaction literature. Moreover, the interacting effects of perceived anthropomorphism and the need for human interaction are unique in the current contextual relations.