An investigation of consumer evaluation of authenticity of their company's CSR engagement

Determinants of CSR and green purchase intention: Mediating role of customer green psychology during COVID-19 pandemic

COVID-19 is a viral disease also comprehended as a coronavirus pandemic that has compelled the world to revisit business strategies to encounter COVID-19 challenges. Over the last decade, ample research has been accomplished on corporate social responsibility (CSR) and circular economy. Nevertheless, a key research gap requires to be filled that how CSR can perform a foremost role in engaging stakeholders like consumers during the COVID-19 era. Drawing from the stakeholder theory, this research endeavors to probe CSR's impact on green purchase intention (GPI) with mediating role of green psychology (GP). Data for the study were gathered from mainland China employing convenience sampling and examined by utilizing SEM (Structural Equation Model). First, the study indicated a direct relationship between CSR and GPI as well as between CSR and GP within three streams, i.e., green trust (GT), green satisfaction (GS), and green perceived value (GPV). It is found that GT, GS, and GPV positively influence GPI whereas the positive mediating relationships of each GP factor were autonomously observed between CSR and GPI, respectively. This research can improve the understanding of the enterprises about consumers and how incorporating green activities may enhance consumers' GPI and GP during the COVID-19 pandemic. This study addresses numerous interesting and insightful implications for strategic management together with certain possibilities for prospective researchers.

Antecedents and Consequences of Banking Customers' Behavior towards Social Media: Evidence from an Emerging Economy

Due to the aggressive competitive climate in practically every sector, modern firms in the digital age confront a variety of hurdles for survival and growth. Technology, mainly digital technology, has altered global business practices. To stay ahead of their competitors, marketers need to develop new strategies that make use of digital technology. Using more conventional forms of competition will not result in spectacular outcomes. In this respect, the rise of social media is a game-changer in marketing since it provides marketers with a strategic touchpoint to engage customers with a brand. Still, it is also important to note the customer's attitude towards social media. Previous studies have, for the most part, ignored the connection between programs involving corporate social responsibility (CSR) and positive experiences for customers. As a result, the current study intends to evaluate the relationship between customer-related CSR activities on social media, customer attitude towards social media, and consumer behavioral outcomes, such as purchase intentions (PI) and electronic word of mouth (E-WOM). Information was collected from banking customers in a developing economy and evaluated with Smart PLS 4.0. According to the findings, customer-related corporate social responsibility activities carried out on social media have an effect on attitudes toward social media, customer behavioral outcomes, such as electronic word of mouth (E-WOM), and buying intentions. The findings also show that a consumer's feelings toward a brand can bridge the gap between customer-related CSR, E-WOM, and purchase intentions. The current study's outcomes can help policymakers comprehend the value of CSR practices from the standpoint of marketing, which is something that most CSR researchers overlook.

What do we know about CSR authenticity? A systematic review from 2007 to 2021

Purpose

This study aims to crystallize the research landscape of corporate social responsibility (CSR) authenticity by systematically analyzing CSR scholarships published in peer-reviewed journals from 2007 to 2021.

Design/methodology/approach

Quantitative content analysis was used to systematically analyze 52 peer-reviewed articles on CSR authenticity. In particular, this study coded the conceptualizations and operationalizations of CSR authenticity, research contexts, applied theoretical frameworks and constructs associated with authenticity in the CSR scholarships.

Findings

This study’s analysis revealed that CSR authenticity is a multifaceted and multidimensional concept researched in various contexts. Yet, it still lacks clear and consistent conceptualization and theorization. Methodologically, qualitative and quantitative methods have equally contributed to the investigation of CSR authenticity. However, scale development and validation still need to improve.

Research limitations/implications

The sample of this research is limited by the searching method and language restriction. This research contributes to CSR scholarships by describing the growing landscape of CSR authenticity research, identifying key research gaps and offering suggestions for future research.

Practical implications

Practitioners can use the findings as references to develop more authentic CSR activities.

Originality/value

This study is an early attempt to examine the research on CSR authenticity, which has been inconclusive and disorganized, despite the rapid growth of publications in recent years.

Creating a Comprehensive Method for the Evaluation of a Company

For investment purposes, the evaluation of a company is not only a matter for a company itself, but also for shareholders and external persons. There are many methods for evaluating a company. This contribution therefore focuses on the creation of a comprehensive method for the evaluation of an industrial enterprise, one that can be used to predict potential future bankruptcies, using a dataset of financial statements of active companies and those in liquidation in the period 2015–2019. Artificial neural networks were used to process the data, specifically logistic regressions from the data processed in the Statistica and Mathematica software programmes. The results showed that the models created using the Mathematica software are not applicable in practice due to the parameters of the obtained results. In contrast, the artificial neural structures obtained using the neural network model in the Statistica software were prospective due to their performance, which is almost always above 0.8, and the logical economic interpretation of the relevant variables. All the generated and retained networks show excellent performance and few errors. However, one of the artificial structures, network no. 4 (MLP 16-16-2), produces better results than the others. Overall, accuracy is almost 81%. In the case of the classification of companies capable of surviving financial distress, accuracy is almost 90%, with that for the classification of companies at risk of going into bankruptcy at nearly 55%.