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The role of retailers in influencing consumer attitude during a brand scandal is quite complex, as retailers are in direct contact with both marketers and consumers. The purpose of the exploratory research is to propose a theoretical model to capture the influences retailers exercise on consumers during brand scandals.

A qualitative approach has been adopted in the study. The study employs the grounded theory approach on the data collected by conducting in-depth interviews with 25 retailers.

Four contextual conditions and six behavioral antecedents of the retailer's role in the context of the brand scandal were identified. Then, the study finds that companies tend to follow two broad approaches during a brand scandal to address retailers' queries and apprehensions. On these bases, the study proposes a six-pronged typology to better understand retailers' role in shaping consumers' brand perception.

Existing literature has not paid adequate attention to this aspect of retailers' role in influencing consumer choices during brand scandal. To the best of the authors' knowledge, there is no prior research which investigates the role and influence of retailers in shaping consumer attitude during brand scandals. It is important to underline that the current research advocates retailers' significant role during a performance-based brand scandal. Specifically, the authors explored a health-related defective scandal of a well-known food brand. In addition, the study focuses on traditional grocery retailers, which already have special relationships with their consumers. Based on retailer perspectives, the authors' contribution is also updating the discussion of branding theory in case of scandals. The identified variables and constructs may be used for empirical investigation on the role of retailers in shaping consumer attitudes toward the scandalized brand.

The purpose of this study is to explore brand customer erosion at both the category and brand levels while considering consumer socio-demographic characteristics and weight of purchase factors.

Data from 3,563 buyers encompassing 20,601 purchases were collected from a prominent household data panel.

Brand customer erosion varies depending on socio-demographic factors (householder age, family size, life cycle and social class) and weight of purchase; variations are evident depending on the specific brand.

The paper makes a substantial contribution to the established fields of marketing and consumer behavior literature by opening a new line of research. It does so by demonstrating, the impact of socio-demographic factors on customer erosion. Simultaneously, it presents results that contradict the limited existing research on the influence of weight of purchase on brand customer erosion.

This article focuses on whether there is a chance to win a World Trade Organization (WTO) trade dispute at the consultation stage. The study suggests an approach to resolving trade disputes on a bilateral level before involving formal WTO resolution procedures.

The model describes the determinants of the probability of winning a trade dispute. The econometric model estimates two different groups of factors available during the consultation period – macroeconomic factors and the institutional features of the trade dispute, such as the number of third parties. The data includes WTO trade disputes from 1995 to 2014.

The suggested model predicts the result of trade disputes with a probability of 76.64%. The research proves that institutional factors such as the number of third parties and the subject of the trade dispute influence the probability of winning.

The results of the study help predict the probability of winning a trade dispute at the consultation stage so that countries can decide whether to pursue a trade dispute.

The research presents several new hypotheses on the results of trade disputes. The authors show that the higher the number of countries involved, the higher the chance of the complainant winning and that if major parties such as the US or the European Union (EU) are involved as third parties, the chance of the complainant winning increases.

This paper aims to analyze how decision support systems manage Big data to obtain value.

A systematic literature review was performed with screening and analysis of 72 articles published between 2012 and 2019.

The findings reveal that techniques of big data analytics, machine learning algorithms and technologies predominantly related to computer science and cloud computing are used on decision support systems. Another finding was that the main areas that these techniques and technologies are been applied are logistic, traffic, health, business and market. This article also allows authors to understand the relationship in which descriptive, predictive and prescriptive analyses are used according to an inverse relationship of complexity in data analysis and the need for human decision-making.

As it is an emerging theme, this study seeks to present an overview of the techniques and technologies that are being discussed in the literature to solve problems in their respective areas, as a form of theoretical contribution. The authors also understand that there is a practical contribution to the maturity of the discussion and with reflections even presented as suggestions for future research, such as the ethical discussion. This study’s descriptive classification can also serve as a guide for new researchers who seek to understand the research involving decision support systems and big data to gain value in our society.

Research about the modern mutually beneficial nonprofit organizations (MBNPOs) has great value because of the increasingly important role that the MBNPO plays in society. The establishment and management of MBNPOs are critical for its development.

Integrated marketing communications (IMC) theory is applied to the research on establishment and management innovation. The establishment of MBNPOs needs four sequential steps: identifying the target group, providing services to meet the demand of stakeholders, designing appropriate communication tactics and deploying proper organizational structure to accomplish efficient communication.

Three types of approach enable traditional enterprises to transform into MBNPOs: product innovation, operational innovation and synergetic development. The application of IMC theory accomplishes management innovation of MBNPOs in three aspects: leading market-orientation specific to stakeholder-orientation, making management innovation systematic in MBNPOs and clarifying targets of management innovation in MBNPOs.

This is one of the first examinations of establishment path and management innovation of MBNPO based on IMC theory.

The ketogenic diet (KD) has gained popularity due to its ability to improve type 2 diabetes, weight loss, antioxidant and anti-inflammatory activity. However, long-term use of the KD might not be safe due to its adverse effects. This study examined the effects of the KD alone or in combination with Zamzam water (holy water for Muslims) on glucose homeostasis, lipid parameters and oxidant-antioxidant variables in rats.

Based on the diet given for ten weeks, three groups of adult male Wistar rats were made (12 rats/group): (1) rats which fed on a chow diet and ordinary water, (2) rats which fed on KD and ordinary water and (3) rats which were given KD along with Zamzam. Fasting blood glucose (FBG), serum insulin, insulin resistance (HOMA-IR), LDL cholesterol, HDL cholesterol, superoxide dismutase and malondialdehyde were compared by one-way ANOVA followed by post-hoc Tukey’s HSD test among groups.

Rats which fed on KD and Zamzam water had significantly reduced FBG and LDL cholesterol compared to the rats which fed on a chow diet and ordinary water (p-values 0.001), and KD and ordinary water (p-value 0.004 and 0.006, respectively). Serum insulin, insulin resistance, HDL cholesterol, superoxide dismutase and malondialdehyde did not differ significantly.

Consumption of KD along with Zamzam for ten weeks significantly reduces FBG and LDL cholesterol. KD alone does not decrease these parameters in ten weeks duration.

Emotional competence supports preschoolers’ social relationships and school success. Parents’ emotions and reactions to preschoolers’ emotions can help them become emotionally competent, but scant research corroborates this role for preschool teachers. Expected outcomes included: teachers’ emotion socialization behaviors functioning most often like parents’ in contributing to emotional competence, with potential moderation by socioeconomic risk. This paper aims to discuss this issue.

Participants included 80 teachers and 312 preschoolers experiencing either little economic difficulty or socioeconomic risk. Children’s emotionally negative/dysregulated, emotionally regulated/productive and emotionally positive/prosocial behaviors were observed, and their emotion knowledge was assessed in Fall and Spring. Teachers’ emotions and supportive, nonsupportive and positively emotionally responsive reactions to children’s emotions were observed during Winter. Hierarchical linear models used teacher emotions or teacher reactions, risk and their interactions as predictors, controlling for child age, gender and premeasures.

Some results resembled those parents’: positive emotional environments supported children’s emotion knowledge; lack of nonsupportive reactions facilitated positivity/prosociality. Others were unique to preschool classroom environments (e.g. teachers’ anger contributed to children’s emotion regulation/productive involvement; nonsupportiveness predicted less emotional negativity/dysregulation). Finally, several were specific to children experiencing socioeconomic risk: supportive and nonsupportive reactions, as well as tender emotions, had unique, but culturally/contextually explainable, meanings in their classrooms.

Applications to teacher professional development, and both limitations and suggestions for future research are considered.

This study is among the first to examine how teachers contribute to the development of preschoolers’ emotional competence, a crucial set of skills for life success.

Process mining (PM) has emerged as a leading technology for gaining data-based insights into organizations’ business processes. As processes increasingly cross-organizational boundaries, firms need to conduct PM jointly with multiple organizations to optimize their operations. However, current knowledge on cross-organizational process mining (coPM) is widely dispersed. Therefore, we synthesize current knowledge on coPM, identify challenges and enablers of coPM, and build a socio-technical framework and agenda for future research.

We conducted a literature review of 66 articles and summarized the findings according to the framework for Information Technology (IT)-enabled inter-organizational coordination (IOC) and the refined PM framework. The former states that within inter-organizational relationships, uncertainty sources determine information processing needs and coordination mechanisms determine information processing capabilities, while the fit between needs and capabilities determines the relationships’ performance. The latter distinguishes three categories of PM activities: cartography, auditing and navigation.

Past literature focused on coPM techniques, for example, algorithms for ensuring privacy and PM for cartography. Future research should focus on socio-technical aspects and follow four steps: First, determine uncertainty sources within coPM. Second, design, develop and evaluate coordination mechanisms. Third, investigate how the mechanisms assist with handling uncertainty. Fourth, analyze the impact on coPM performance. In addition, we present 18 challenges (e.g. integrating distributed data) and 9 enablers (e.g. aligning different strategies) for coPM application.

This is the first article to systematically investigate the status quo of coPM research and lay out a socio-technical research agenda building upon the well-established framework for IT-enabled IOC.

This systematic review paper aims to investigate seasonal ambient change’s impact on the incidence of falls among older adults.

The population, exposure, outcome (PEO) structured framework was used to frame the research question prior to using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis framework. Three databases were searched, and a total of 12 studies were found for inclusion, and quality appraisal was carried out. Data extraction was performed, and narrative analysis was carried out.

Of the 12 studies, 2 found no link between seasonality and fall incidence. One study found fall rates increased during warmer months, and 9 of the 12 studies found that winter months and their associated seasonal changes led to an increase in the incidence in falls. The overall result was that cooler temperatures typically seen during winter months carried an increased risk of falling for older adults.

Additional research is needed, most likely examining the climate one lives in. However, the findings are relevant and can be used to inform health-care providers and older adults of the increased risk of falling during the winter.

Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.