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The present study, by using signaling perspective aims to investigate short-term valuation impact of rebranding announcements (with name change) on stock performance of 160 service firms listed on NSE NIFTY-500 over the period of 2000–2019.

An event study methodology is used to estimate the cumulative abnormal returns (CARs) and its statistical significance is tested with both parametric and non-parametric test-statistics. Separate analysis has been conducted for firms with “major vs minor” and “restructuring vs non-restructuring” name change.

Findings of the study suggest that rebranding decisions are negatively associated with abnormal returns around the announcement period indicating strong disapproval of name change event. In addition, investors formed strong adverse opinion for major name change firms as compared to minor name change firms. Further, restructured name change sample document larger negative drift than non-restructured sample.

Findings offer substantial repercussions for shareholders who can make informed judgments about name change as a signal of reinventing brand identity. Managers should announce detailed rationale behind name change decision to market for enhancing corporate reputation.

This study contributes to marketing-finance interface literature and is first to examine market reaction to name change of Indian service firms and moreover, made a distinction between major vs minor and restructured vs non-restructured name change events for these firms.

This study aims to conduct a geographical analysis of the distribution and type of activities developed by social enterprises in rural and urban areas of Ireland.

The study analyses data of more than 4,000 social enterprises against a six-tier rural/urban typology, using descriptive statistics and non-parametric tests to test six hypotheses.

The study shows a geographical rural–urban pattern in the distribution of social enterprises in Ireland, with a positive association between the remoteness of an area and the ratio of social enterprises, and a lack of capital-city effect related to the density of social enterprises. The analysis also shows a statistically significant geographical rural–urban pattern for the types of activities developed by social enterprises. The authors observe a positive association between the remoteness of the areas and the presence of social enterprises operating in the community and local development sector whereas the association is not significant for social enterprises developing welfare services.

The paper shows the potential of using recently developed rural–urban typologies and tools such as geographical information systems for conducting geographical research on social enterprises. The findings also have implications for informing spatially sensitive policymaking on social enterprises.

The merging of a large national data set of social enterprises with geographical tools and data at subregional level contributes to the methodological advancement of the field of social enterprises, providing tools and frameworks for a nuanced and spatially sensitive analysis of these organisations.

This study explores whether the unique organizational form of family firms helps to mitigate the negative effects caused by the announcement of product recalls.

The authors use an event study, for a sample of 2,576 product recalls in the United States (US) automobile industry, between January 2010 and June 2021.

The authors found that stock market's reaction to a product recall announcement is less negative for family firms. This superior performance is partially driven by the family firms' long-term investment horizons and higher strategic emphasis on product quality. However, the relationship between family ownership and cumulative abnormal returns around product recall announcements is nonlinear as the impact of family ownership starts by being positive but becomes negative for higher levels of family ownership. The authors also find that family firm's chief executive officer (CEO) and managerial ownership influence positively the stock market reaction to product recall announcements.

This work has several implications for family firms' management as well as for investors and financial analysts. First, as higher managerial ownership is associated with a greater emphasis on product quality, decreasing stock market losses when a product recall occurs, family firms should consider increasing equity-based compensation. Second, as there seems to exist an optimal proportion of family ownership, family firms should consider the risks of increasing too much their ownership share. Third, investors and financial analysts can use the results in the study to help them in their investment and trading decisions in the stock market.

The authors extend the knowledge of product recalls by studying the under-researched role of the flexible, internally focused culture of family businesses on the stock market reaction to product recalls.

This chapter investigates pandemic impact in a variety of industries, including food, travel, education and pharmaceuticals, considering elements such as isolation, emotions and social influences, which can lead to panic buying. The goal of this research is to ascertain how COVID-19 influences the buying decisions of customers. Additionally, the study aims to identify consumer consumption trends for a spectrum of products and services, including fast-moving consumer goods (FMCGs), entertainment, pharmaceuticals, travel and tourism. A comprehensive review of different research papers is done to conclude. The papers considered are from 2020 to 2022. Different keywords are used to search the relevant papers such as ‘pandemic’, ‘COVID-19’, ‘behaviour’, ‘impulsive’, etc. TCCM framework has been applied while reviewing the articles. During the isolation, consumer behaviour moved to panic buying and stockpiling, favouring organic basics, and encouraging e-commerce, as well as economic nationalism favouring made-in-India products. This study helps in knowing the reasons for change in consumers' behaviour for different products and services due to unforeseeable situations like COVID-19 and can find possible ways to deal with them. Business owners learn about changing consumer purchasing behaviours and how to modify products. The government can change policies to improve medical tourism and social protection.

Nowadays, nations are rapidly changing and evolving, both because of global competitiveness and technological development. The fast change of the economies and the interconnected world has brought a more globalized world than ever. The purpose of this paper is to assess Romania (RO) and Türkiye (TR) by using a customized version of Porter’s diamond model (PDM), with an emphasis on identifying the key components of their innovation systems.

The paper uses a recognized model to unfold its structure. Based on the PDM, this paper tackles the topic of innovation systems both of RO and TR. Applying the model, a mapping of indicators representing components of the national innovation system is made possible. Besides the traditional four determinants (dimensions) of the model, the authors adapted it and added the technology conditions. Using the five dimensions, a comparison of strategical objectives is made between RO and TR.

The results show the potential for both countries to develop and embrace the innovation capacity, while there is still room for improvement in this regard. Another point is the map of innovation system components that were used for the comparison. The implications of innovation are analyzed at a strategical level, comparing the mapping with the national strategical objectives.

There are many studies using this model, however a few bring into the light the impact of innovation systems at national level. Hence, a new framework is provided to evaluate innovative systems using a selection of modern indicators. This study uses an existing model in literature, Porter’s model mapping indicators, which highlight the innovation capacity.

Professional and corporate codes of ethics (Codes) are commonly used, but they are not consistently effective. Research has indicated the importance of values included in Codes, but there is little research exploring how to improve the effectiveness of Code values. There are proven pedagogies that can be used in ethics training, notably, the values-focused approach known as value self-confrontation (VSC). VSC comes from the field of psychology and has been researched for over 50 years. This theory-based methodology is effective at increasing the importance of targeted values and positively changing attitudes and behaviors. Based on our thematic review of extant VSC literature, we develop a simplified VSC implementation strategy and instrument called code value self-confrontation (CVSC). CVSC involves a self-confrontation between a participant’s personal values and the values of the organization. This confrontation can create value dissonance in the participant, which can increase the importance given to the values of the organization. VSC has been effective at positively impacting pro-organization behaviors as well as societal issues such as equality, race relations, and environmentalism. By increasing the importance of ethical values, organizations can be rewarded with behavioral changes that translate into more ethical work behaviors and decision-making.

Over the last two decades, there has been a significant increase in incivility within the higher education sector, potentially due to mounting pressure and demands on academics, both collectively and individually. The effects on various aspects of academia, such as knowledge and learning, however, remain largely unexplored. The purpose of this research is to fill the gap by performing a theoretical trend analysis and subsequently empirically investigating the impact of workplace incivility on research scholars’ learning engagement and knowledge sharing intentions, including the mediating role of self-esteem.

This study uses a three-stage methodological process: first, a thorough theoretical (bibliographic) analysis of scientific publications, using Biblioshiny, to identify the trends of workplace incivility; second, an empirical, qualitative exploration of the emergent themes and subthemes based on 102 in-depth interviews with research scholars, using NVivo 12 Plus; and third, quantitative testing, using 154 responses and structural equation modeling.

The authors verify a visible negative association between incivility and learning engagement, incivility and knowledge sharing intentions as well as self-esteem’s mediating effect on this relationship. Also, the thematic analysis revealed three distinct themes: the type of incivility; reasons for such incidences; and the impact of such incidences on research scholars.

The research bears implications both to theory and practice. Regarding the former, the gravity and graveness of incivility versus knowledge and learning, within the academic workplace environment, are not simply highlighted, but analyzed and refined, with explicit findings of both scholarly and practicable worth; that also provide solid foundations and avenues for future research.

Further to its primary findings, the research contributes to extant knowledge by elucidating and explicating the topic, both theoretically and empirically, as well as by presenting implications for theory and practice. Regarding practical implications, this research sheds light on how to develop an appropriate organizational culture that facilitates learning engagement and increases knowledge sharing intentions, by nurturing the identified explicit and underlying motivators of civility.

The purpose of the study would typically involve investigating how the ongoing COVID-19 pandemic has impacted the learning abilities of university students. The study could encompass various factors that may influence students' ability to learn, such as their academic performance, motivation, engagement, mental health, access to resources and learning environment.

1. A cross-sectional design, collecting data at a specific point in time to capture the impact of the COVID-19 pandemic on students' learning abilities. 2. A structured questionnaire will be developed based on relevant literature and research objectives. 3. The questionnaire could be administered to the targeted sample of university students through online surveys, email or other appropriate methods. 4. Descriptive statistics could be used to summarize the demographic characteristics and other relevant variables of the sample. Factor analysis could be performed to identify underlying factors. The Mann–Whitney test, a non-parametric test, could be used to compare the differences between groups.

The results of the data analysis would be interpreted and discussed in the context of the research objectives and relevant literature. The findings could provide insights into the factors that significantly affect learning abilities during the COVID-19 pandemic and highlight any differences among groups. Limitations of the study, such as sample size or potential biases, would also be discussed.

The study would provide a comprehensive overview of the impact of the COVID-19 pandemic on university students' learning abilities, highlight the existing literature in the field and establish the need for further research to investigate the factors influencing students' learning abilities during the pandemic. The study can provide a solid framework for similar studies.

Lean construction (LC) is an innovative approach in the construction industry that has shown significant success in developed countries. Although LC has potential in the construction sector of Pakistan, it has not been extensively explored. This study aims to address this knowledge gap by identifying and predicting current lean practices and assessing the strengths and weaknesses of LC implementation in Pakistan.

Using robust statistical methods to analyze 92 valid responses, the study reveals that approximately 54% of lean practices are currently in use in the construction industry of Pakistan, with a population mean ranging from 52.7% to 55.6%.

Surprisingly, the research identifies instances where some construction firms in Pakistan are implementing LC practices, even though they have only a limited understanding of its underlying principles. Notably, certain subprinciples, such as visual management, top management commitment to change, employee training, process cycle time reduction and production optimization, are less integrated within the construction industry. Exploring the possibility of implementing LC, recommendations for strategies to implement LC in Pakistan are suggested, aligning with the conceptual model proposed by the researchers.

The novelty of this work offers insights that can serve as a comprehensive guide for developing nations. It provides a structured approach to assess and benchmark LC practices, which, in turn, can contribute to a more efficient and effective construction industry. Moreover, the strategies proposed in this research can aid developing countries in the efficient implementation of LC. This will have a positive implication for both economic and developmental outcomes.

Recent evidence from a linear econometric framework infers that housing search activity, captured from Google Trends data, can predict housing returns for the USA at a national and regional (metropolitan statistical area [MSA]) level. Based on search theory, the authors, however, postulate that search activity can also predict housing returns volatility. This study aims to explore the possibility of using online search activity to predict both housing returns and volatility.

Using a k-th order non-parametric causality-in-quantiles test allows us to test for predictability in a robust manner over the entire conditional distribution of both housing price returns and its volatility (i.e. squared returns) by controlling for nonlinearity and structural breaks that exist in the data.

The analysis over the monthly period of 2004:01 to 2021:01 produces results indicating that while housing search activity continues to predict aggregate US house price returns, barring the extreme ends of the conditional distribution, volatility is relatively strongly predicted over the entire quantile range considered. The results carry over to an alternative (the generalized autoregressive conditional heteroskedasticity-based) metric of volatility, higher (weekly)-frequency data (over January 2018–March 2021) and to over 84% of the 77 MSAs considered.

To the best of the authors’ knowledge, this is the first study regarding predictability of overall and regional US housing price returns and volatility using search activity, based on a non-parametric higher-order causality-in-quantiles framework, which is insightful to investors, policymakers and academics.