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Existing studies have focused on shoppers’ characteristics, highlighting a gap in research in terms of considering e-retailers’ characteristics. Accordingly, this study aims to map e-retailer characteristics and their effect on (a) satisfaction and regret and (b) the intentions to write a review and repurchase intention. Moreover, this research also explores the role of confirmation as a moderator.

The present paper utilises a hierarchical regression technique and structured equation modelling to test the conceptual framework with 400 responses. The hypotheses were tested with shoppers of two leading e-commerce firms, namely Amazon and Flipkart.

This study highlights several differences in the characteristics of e-retailers and their impact on buyers’ satisfaction and regret. Furthermore, a few discrepancies are observed in the case of shoppers’ post-purchase behavioural intentions to write reviews and repurchase intention.

Based on the findings, the research presents implications for e-retailers, including Amazon and Flipkart.

This study attempted to measure life satisfaction and developed a scale to measure its dimensions with the required psychometric properties (validity and reliability). In today’s scenario, organizations are focusing on life satisfaction by helping employees to maintain their work-life balance. Therefore, this paper aims to develop a robust scale of life satisfaction.

The methodology consists of three broad stages: item generation, scale development, and validity. Using the sample of 198 working executives, this study used the exploratory factor analysis (EFA) and concluded the four dimensions of life satisfaction: work satisfaction, family satisfaction, societal satisfaction and self-satisfaction.

The results provide academicians and practitioners with new insight and dimensions of life satisfaction. The result of this study shows that life satisfaction has societal satisfaction, family satisfaction, job satisfaction and self-satisfaction dimensions.

This study will provide practitioners with new dimensions to measure life satisfaction. They can help employees achieve life satisfaction across four different factors. This will enable more employee satisfaction, an increase in retention rate and an increase in employee performance. Furthermore, this study provides implications from a policy perspective to design the business policy by considering life satisfaction as an important part of formulating and implementing human resource policies.

This study is unique in terms of exploring the dimensions of life satisfaction in a structured manner and establishing the psychometric properties as construct, content, and criterion validity along with reliability. This scale can be further used in future research to measure the life satisfaction construct.

This study aims to examine various facets of entrepreneurial orientation (EO), including innovativeness, proactiveness and risk-taking. It investigates their linkage to the performance of new ventures. It further analyzes the mediating role of innovation ambidexterity.

The study uses a judgmental sampling technique to gather data from 342 new ventures. The analysis is conducted using PLS-SEM to predict the potential consequences of EO on new venture performance (NVP) through ambidextrous innovation.

The results show that innovation ambidexterity mediates between EO and NVP. New ventures should explore new opportunities for long-term growth while exploiting the existing opportunities for short-term growth and survival.

The research focuses on interpreting how different EO components are related to innovation ambidexterity. It also investigates what role of innovation ambidexterity plays as a mediator in the correlation of EO–NVP. It expands the current discussion on EO–venture performance plus innovation ambidexterity considering new ventures in emerging economies.

Business research has highlighted the importance of knowledge transfer and innovation in multinational firms for better performance outcomes. However, the existing body of literature is characterized by differentiated theories, antecedents and outcomes. This study aims to address this gap by adopting a systematic approach to analyze knowledge transfer and innovation literature from the perspective of multinational organizations.

This study follows “preferred reporting items for systematic reviews and meta-analyses” (PRISMA) guidelines for conducting a systematic literature review. The study adopts a systematic approach for analyzing the literature using School of thought (S), Contexts (C), Methodologies (M), Triggers (T), Barriers (B), Facilitators (F) and Outcomes (O) framework (SCM-TBFO framework) devised for holistic literature review. The study analyzes 75 articles from reputed journals from 2000 to 2022.

In general, knowledge transfer and innovation in multinationals is a relatively new area and is evolving rapidly. There are many opportunities to study the various perspectives that are included in the SCM-TBFO framework. The key schools of thought included the evolutionary theory of innovation, institutional theory and internationalization theory. The studies had differing settings or contexts, including China, Europe, the USA and Taiwan. Further, key methodologies that were used included regression, case studies, structural equation modeling (SEM) and theoretical studies. Knowledge transfer and innovation triggers included competitive advantage, competitive pressure, constant requirements for better products and services, foreign direct investment (FDI) and globalization. Knowledge transfer and innovation facilitators were categorized into strategy-related facilitators, organization culture and orientation-related facilitators, and resource-related facilitators. Knowledge transfer and innovation barriers included autonomy, international knowledge dispersion, risk of knowledge leakage, search breadth, ambiguity and institutional voids. Key outcomes of knowledge transfer and innovation in multinationals included financial performance, innovation performance, knowledge flow, transfer effectiveness, patents and new product development.

By synthesizing the literature, the study aims to provide an overview of the current state of research on knowledge transfer and innovation in multinationals. The study develops a holistic model for fostering knowledge transfer and innovation in multinationals. The proposed novel framework can also be applied to perform a holistic assessment of the current literature in various research domains. Further, the study suggests future theory development and research agendas. The study also provides implications for practitioners using the framework to achieve more desirable outcomes.

The paper aims to identify, analyse and develop a model for measuring the inter-relationship and interaction among the antecedents influencing innovation implementation. The extant literature has not widely studied the interactions and inter-relationships among the antecedents of innovation implementation. To fill this gap, the paper develops a hierarchical relationship framework between the identified antecedents of innovation implementation.

The study follows mixed method-based approach using two methodologies: modified total interpretive structural modelling (m-TISM) and MICMAC (Matriced’ Impacts Croisés Multiplication Appliquée á un Classement) analysis. m-TISM is used for the purpose of establishing the hierarchical relationship among the antecedents. MICMAC analysis is used to study the driver-dependent relationship. To identify the antecedents of innovation implementation, the paper follows a systematic search method found in the review articles. The article search was performed across different databases including Google Scholar, Web of Science, EBSCO and Scopus.

In this study, eight innovation implementation antecedents are identified. The analysis indicates that competency antecedents such as leader competency and employee competency, having high driving and weak dependence power, are at the lowest level in the hierarchical model, whereas, innovation implementation, having high dependence and low driving power, is at the highest level in the hierarchical model. Strategic resources act as a linkage variable.

Although this study summarizes the extant literature to generalize the findings, the future studies can focus upon statistical validation of model by employing structural equation modelling to generalize the results.

The practitioners must emphasize on antecedents having strong driving power for successful implementation of innovation. The hierarchical model is proposed for implementing innovation successfully that will help organizations to be more competitive, productive and profitable.

In this study, m-TISM and MICMAC-based hierarchical models are proposed for implementing innovation successfully in organizations. It also provides the variables insights such as driver-dependent interrelationship between the identified antecedents.

This study aims to identify the antecedents of strategic thinking and its relationship with competitive advantage. Further, this study analyses the mediating effect of strategic thinking between its antecedents and competitive advantage.

A self-reported questionnaire with 51 questions was floated among 220 professionals from various industries in India. The response was analysed using the partial least squares-structural equation modelling methodology using SmartPLS software.

The direct effect of creativity, corporate culture and knowledge management are established with strategic thinking, as well as a competitive advantage. Also, the study finds a significant relationship between strategic thinking and competitive advantage. The study finds no mediation (direct effect) in the case of creativity, corporate culture and knowledge management. Further, no mediation (no relationship) is found in the case of vision.

Business must start adopting strategic thinking practices in their decision-making process to create a competitive advantage. Further, the influence of corporate culture, creativity and knowledge management on strategic thinking highlights their importance.

The study establishes the impact of antecedents of strategic thinking on competitive advantage. The study highlights the importance of other factors along with strategic thinking for achieving competitive advantage.

Assessing the antecedents of innovation implementation holds importance for companies, as previous studies have shown that without proper implementation the innovation is doomed to fail. Over the past few years, research on innovation implementation is growing. However, the evidence on the antecedents of innovation implementation is inconsistent. The purpose of the study is to conduct a review of the literature using meta-analysis to summarize the divergent views present in the literature.

A meta-analysis technique is adopted for reviewing the literature. The literature search was conducted with selected keywords in different databases and top journals from the ABDC list (A* and A).

The results of the meta-analysis that summarize evidence from 42 papers, 100 effect sizes and 32,223 organizations show the significance and homogeneous/heterogeneous opinions of the past studies. Results reveal the homogeneity in antecedents such as transformational leadership, business collaboration, employee competency, leader competency, absorptive capacity and business size and heterogeneity in the antecedents such as communication, customer collaboration, internal entrainment, external entrainment, implementation climate and strategic resources.

The results imply that managers attempting to implement innovation in the organizations need to first focus on homogenous antecedents followed by heterogeneous antecedents for successful implementation.

This study advocates research on innovation implementation. It tests the significance, nature of the relationship and summarizes the divergent views on antecedents of innovation implementation in an organization. The results of this study can also be used in the theoretical advancement of management innovation literature.

The purpose of this paper is to use Twitter analytics for analyzing the startup ecosystem of India.

The paper uses descriptive analysis and content analytics techniques of social media analytics to examine 53,115 tweets from 15 Indian startups across different industries. The study also employs techniques such as Naïve Bayes Algorithm for sentiment analysis and Latent Dirichlet allocation algorithm for topic modeling of Twitter feeds to generate insights for the startup ecosystem in India.

The Indian startup ecosystem is inclined toward digital technologies, concerned with people, planet and profit, with resource availability and information as the key to success. The study categorizes the emotions of tweets as positive, neutral and negative. It was found that the Indian startup ecosystem has more positive sentiments than negative sentiments. Topic modeling enables the categorization of the identified keywords into clusters. Also, the study concludes on the note that the future of the Indian startup ecosystem is Digital India.

The analysis provides a methodology that future researchers can use to extract relevant information from Twitter to investigate any issue.

Any attempt to analyze the startup ecosystem of India through social media analysis is limited. This research aims to bridge such a gap and tries to analyze the startup ecosystem of India from the lens of social media platforms like Twitter.

The primary aim of this study is to detail the use of soft computing techniques in business and management research. Its objectives are as follows: to conduct a comprehensive scientometric analysis of publications in the field of soft computing, to explore the evolution of keywords, to identify key research themes and latent topics and to map the intellectual structure of soft computing in the business literature.

This research offers a comprehensive overview of the field by synthesising 43 years (1980–2022) of soft computing research from the Scopus database. It employs descriptive analysis, topic modelling (TM) and scientometric analysis.

This study's co-citation analysis identifies three primary categories of research in the field: the components, the techniques and the benefits of soft computing. Additionally, this study identifies 16 key study themes in the soft computing literature using TM, including decision-making under uncertainty, multi-criteria decision-making (MCDM), the application of deep learning in object detection and fault diagnosis, circular economy and sustainable development and a few others.

This analysis offers a valuable understanding of soft computing for researchers and industry experts and highlights potential areas for future research.

This study uses scientific mapping and performance indicators to analyse a large corpus of 4,512 articles in the field of soft computing. It makes significant contributions to the intellectual and conceptual framework of soft computing research by providing a comprehensive overview of the literature on soft computing literature covering a period of four decades and identifying significant trends and topics to direct future research.