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In a first of its kind, this paper tries to explore the long-run relationship between investors' sentiment and selected industries' returns over the period January 2010 to December 2021.

The paper uses 23 market and macroeconomic proxies to measure investor sentiment. Principal component analysis has been used to create sentiment sub-indices that represent investor sentiment. The autoregressive distributed lag (ARDL) model and other sophisticated econometric techniques such as the unit root test, the cumulative sum (CUSUM) stability test, regression, etc. have been used to achieve the objectives of the study.

The authors find that there is a significant relationship between sentiment sub-indices and industries' returns over the period of study. Market and economic variables, market ratios, advance-decline ratio, high-low index, price-to-book value ratio and liquidity in the economy are some of the significant sub-indices explaining industries' returns.

The study has relevant implications for retail investors, policy-makers and other decision-makers in the Indian stock market. Results are helpful for the investor in improving their decision-making and identifying those sentiment sub-indices and the variables therein that are relevant in explaining the return of a particular industry.

The study contributes to the existing literature by exploring the relationship between sentiment and industries' returns in the Indian stock market and by identifying relevant sentiment sub-indices. Also, the study supports the investors' irrationality, which arises due to a plethora of behavioral biases as enshrined in classical finance.

This study aims to identify the legitimacy issues raised during a sustainable business model innovation, deployed by an Italian company, which was analyzed through the lens of the legitimation theory and the business model innovation theory.

A single case study methodology is employed for empirical research. Semistructured interviews, with top and middle management, were conducted together with the analysis of several internal and external documents, to corroborate the case analysis.

Results show how the potentiality of digital technologies allows the development of new sustainable business models, which, though, still need to gain legitimation to be accepted. The study findings allow drawing both on the business model innovation theory and on the legitimation theory, as they show how legitimation is a dynamic concept that involves internal as well as external stakeholders to support business model innovation.

The paper is novel, since it addresses the topic of sustainable business models development, showing how companies can get legitimation. The paper builds on existing theories and provides a practical example.

The objective of this study is to examine current business and management research on “Industry 4.0 base technologies” and “business models” to shed light on this vast literature and to point out future research agenda.

The authors conducted a bibliometric analysis of scientific publications based on 482 documents collected from the Scopus database and a co-citation analysis to provide an overview of business model studies related to Industry 4.0 base technologies. After that a qualitative analysis of the articles was also conducted to identify research trends and trajectories.

The results reveal the existence of five research themes: smart products (cluster 1); business model innovation (cluster 2); technological platforms (cluster 3); value creation and appropriation (cluster 4); and digital business models (cluster 5). A qualitative analysis of the articles was also conducted to identify research trends and trajectories.

First, the dataset was collected through Scopus. The authors are aware that other databases, such as Web of Science, can be used to deepen the focus of quantitative bibliometric analysis. Second, the authors based this analysis on the Industry 4.0 base technologies identified by Frank et al. (2019). The authors recognize that Industry 4.0 comprises other technologies beyond IoT, cloud computing, big data and analytics.

Drawing on these analyses, the authors submit a useful baseline for developing Industry 4.0 base technologies and considering their implications for business models.

In this paper, the authors focus their attention on the relationship between technologies underlying the fourth industrial revolution, identified by Frank et al. (2019), and the business model, with a particular focus on the developments that have occurred over the last decade and the authors performed a bibliometric analysis to consider all the burgeoning literature on the topic.

This study investigates the effectiveness of microfinance-backed entrepreneurship as a mechanism for the holistic empowerment of women.

This study employs a mixed-method research-design consisting of quasi-experimental design (quantitative approach) involving women, both entrepreneurs (132) and non-entrepreneurs (238), as well as in-depth semi-structured interviews (qualitative approach).

Quantitative analysis revealed that female entrepreneurs are better off than female non-entrepreneurs in terms of economic, social, political and psychological indicators of empowerment. However, relatively lesser impact was found in terms of political, and to an even smaller extent, social empowerment of women. Analysis of in-depth interviews corroborated these findings confirming that entrepreneurship serves as an effective tool for the holistic empowerment of women. However, non-entrepreneurs also exhibit social empowerment.

Given the restricted geographical ambit of the study, prudence ought to be exercised in drawing inferences applied to alternate contexts. That the vast majority of questionnaire respondents are illiterate presented a notable impediment in the process of collection of accurate responses.

Microfinance intervention ought to be specifically directed to cultivating entrepreneurship among women; in particular, to achieve the full benefits of empowerment, women availing microfinance ought to exert full control over their own business ventures.

In analyzing holistic empowerment through microfinance supported businesses set up by women, the study adds to the existing literature on women entrepreneurship and empowerment.

Current online business development redistributes last-mile logistics (LML) from consumer to retailer and producer. This paper identifies how empirical LML research has used and defined logistic performance measures for key grocery industry actors. Using a multi-actor perspective on logistic performance, the authors discuss coordination issues important for optimising LML at system level.

A semi-systematic literature review of 85 publications was conducted to analyse performance measurements used for effectiveness and efficiency, and for which actors.

Few empirical LML studies exist examining coordination between key actors or on system level. Most studies focus on logistic performance measurements for retailers and/or consumers, not producers. Key goals and resource utilisations lack research, including all key actors and system-level coordination.

Current LML performance research implies a risk for sub-optimisation. Through expanding on efficiency and effectiveness interplay at system level and introducing new research perspectives, the review highlights the need to revaluate single-actor, single-measurement studies.

No established scientific guidelines exist for solving LML optimisation in the grocery industry. For managers, it is important to thoroughly consider efficiency and effectiveness in LML execution, coordination and collaboration among key actors, avoiding sub-optimisations for business and sustainability.

The study contributes to current knowledge by reviewing empirical research on LML performance in the grocery sector, showing how previous research disregards the importance of multiple actors and coordination of actors, efficiency and effectiveness.