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Mergers and acquisitions, corporate strategy.

This case could be applied in several courses: a mergers and acquisitions (M&A) course, to introduce the various motives for firms doing M&A, a strategy course exploring a company's strategy exploration and decision processes, or in a marketing course as an example about emerging and global market interaction. The target audience is primarily final year or Masters' and MBA students. It would also be useful for executive education seminars.

The Case provides learning opportunities about how companies encounter threats due to changing market or fiscal conditions, find ways to address their individual challenges yet achieve mutual benefit, by taking advantage of market-induced opportunities for strategic change, which have been triggered by a combination of situational factors.

The case can be used to illustrate and discuss several important aspects of the growth of companies in emerging markets, including: motives for making M&As; strategic options and selection in the emerging industry; and how regional firms can respond to globalization.

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The study employs two independent experimental studies to collect data. It focuses on the matching effect between advertising appeals and product types. The Elaboration Likelihood Model serves as the theoretical framework for understanding the cognitive processing involved in consumers' responses to these advertising appeals and product combinations.

This paper aims to investigate the impact of advertising appeals on consumers' intentions to purchase organic food. We explored the interaction between advertising appeals (egoistic vs altruistic) and product types (virtue vs vice) and purchase intention. The goal is to provide insights that can enhance the advertising effectiveness of organic food manufacturers and retailers.

The analysis reveals significant effects on consumers' purchase intentions based on the matching of advertising appeals with product types. Specifically, when egoistic appeals align with virtuous products, there is an improvement in consumers' purchase intentions. When altruistic appeals match vice products, a positive impact on purchase intention is observed. The results suggest that the matching of advertising appeals with product types enhances processing fluency, contributing to increased purchase intention.

This research contributes to the field by providing nuanced insights into the interplay between advertising appeals and product types within the context of organic food. The findings highlight the importance of considering the synergy between egoistic appeals and virtuous products, as well as altruistic appeals and vice products. This understanding can be strategically employed by organic food manufacturers and retailers to optimize their advertising strategies, thereby improving their overall effectiveness in influencing consumers' purchase intentions.

Open innovation (OI) has become increasingly popular as an enterprise strategy in both industry and academia, and has been adopted, at least in part, by many companies. Despite this popularity, there is a dearth of evaluation of OI efficiency and a lack of suitable quantitative indices. The paper aims to discuss these issues.

In this study, the authors used both data envelopment analysis (DEA) and Malmquist techniques to compare the pre- and post-transition levels of performance achievement of Procter & Gamble (P&G), a widely recognised and public early adopter of OI, with a group of its main competitors.

Most detailed analysis of the time-course revealed that the innovation efficiency of P&G improved rapidly and substantially after its embracing of OI, an effect we term the “open rise”. However, there is also a transient decline in R&D efficiency at the beginning of OI adoption (“open dip”) and an unexpected and marked decline (“open drop”) after the peak positive effect.

The quantitative methods appear to meet the needs identified in the preceding literature for more quantitative approaches to the measurement of OI.

The aim of this study was to analyze the effects of carbon reduction efforts and preservation efforts on system benefits in the cold chain industry of fresh products.

This study develops an optimal decision game model for the fresh products in the cold chain, incorporating the retailer's preservation effort and the supplier's carbon emission reduction effort. It quantifies the relationship between carbon emission reduction effort, preservation effort and system profit. The model considers parameters like carbon trading price, consumer low-carbon preference and consumer freshness preference, reflecting real-world conditions and market trends. Numerical simulations are conducted by varying these parameters to observe their impact on system profit.

Under the carbon cap-and-trade policy, the profit of the fresh cold chain system is higher than that of the fresh cold chain system without carbon constraints, and the profit of the supplier under decentralized decision-making is increased by nine times in the simulation results. The increase in carbon trading prices can effectively improve the freshness level of fresh products cold chain, carbon emission reduction level and system profit.

This study comprehensively considers the factors of freshness and carbon emission reduction, provides the optimal low-carbon production decision-making reference for the fresh food cold chain and promotes the sustainable development of the fresh food cold chain.

The purpose of the research is to assess the risk of the financial market in the digital economy through the quantitative analysis model in the big data era. It is a big challenge for the government to carry out financial market risk management in the big data era.

In this study, a generalized autoregressive conditional heteroskedasticity-vector autoregression (GARCH-VaR) model is constructed to analyze the big data financial market in the digital economy. Additionally, the correlation test and stationarity test are carried out to construct the best fit model and get the corresponding VaR value.

Owing to the conditional heteroscedasticity, the index return series shows the leptokurtic and fat tail phenomenon. According to the AIC (Akaike information criterion), the fitting degree of the GARCH model is measured. The AIC value difference of the models under the three distributions is not obvious, and the differences between them can be ignored.

Using the GARCH-VaR model can better measure and predict the risk of the big data finance market and provide a reliable and quantitative basis for the current technology-driven regulation in the digital economy.

This study aims to conduct a “real-time” investigation with user-generated content on Twitter to reveal industry challenges and business responses to the coronavirus (Covid-19) pandemic. Specifically, using the hospitality industry as an example, the study analyses how Covid-19 has impacted the industry, what are the challenges and how the industry has responded.

With 94,340 tweets collected between October 2019 and May 2020 by a programmed Web scraper, unsupervised machine learning approaches such as structural topic modelling are applied.

This study contributes to the literature on business response during crises providing for the first time a study of using unstructured content on social media for industry-level analysis in the hospitality context.

The purpose of this paper is to employ a quantitative approach to explore the intellectual structure of the market orientation (MO) field over the course of its development.

This research was conducted by using the bibliometric techniques of citation and co-citation analyses to investigate 1,892 publications in the MO field from 1990 to 2016, as well as factor analysis and multidimensional scaling to present a clear visual experience of the knowledge structure of the MO filed.

This study reveals meaningful outputs to assist in: delineating the critical authors, institutions and countries related to the study of MO; identifying the published documents that have had a significant influence on the field; clarifying the subfields that have developed from the MO field; and mapping the intellectual structure of the field in a two-dimensional space that allows for the visual representation of different themes.

Given the sheer volume of works that exist, these bibliometric techniques cannot completely measure, describe and present the entire intellectual structure of the MO field. Instead, co-citation analysis was performed using the data from only the top publications to identify the level of integration of the field, the changes of each knowledge group and the maturity of its evolution.

First, this study extends the approach to identify the subject of MO from a quantitative perspective. Second, our analysis shows the intersection between the marketing discipline and management discipline in the MO literature. Finally, this study reveals the development tendency of the MO field in recent years. The results of this study are valuable to readers interested in MO research, especially those newly interested in this field.

The increasing focus of consumers on health and environmental sustainability continues to drive the demand for organic food. Despite the recognized importance of health and environmental concerns, the differential impact of these factors on organic food purchasing decisions is evident, indicating the presence of moderating variables. This investigation attempts to delineate these contingencies within the realms of socio-environmental and individual factors, paying particular attention to subjective norms, uncertainty, and egoistic values.

Using the convenience sampling method, the primary data sample was collected by a professional market research consulting firm and included 1876 usable respondents from China. Hierarchical multiple regression analysis was utilized to verify the model and test the relationships between the constructs.

The results indicated that the path from environmental concern to organic food purchase intention was significantly influenced by subjective norms and uncertainty, both of which enhance this relationship. In contrast, egoistic values appeared to dampen this effect. Uncertainty also emerged as a key factor in the link between health concerns and organic food purchase intention, albeit with an opposite impact, weakening the relationship.

This study provides useful insights for academics and marketers to understand the complex phenomenon of organic consumer behavior. This result indicates that marketers can target reference groups to develop organic food marketing strategies.

Few studies have proposed and validated a model with these moderating factors collectively to study the purchase intention of organic food consumers in China.