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This paper examines in detail how the use of storytelling with parallax technology can influence the user experience (UX) in online shops as well as brand- and behavior-relevant variables. Furthermore, this study analyzes the causal relationships between UX, brand attitudes and brand-related behavioral intentions in terms of purchase intention and price premiums. Explicit and implicit paths of human information processing are considered.

A sample of 266 respondents completed a web-based experiment under two conditions (text-based vs parallax storytelling online shop). An existing and operational online shop was used. The causal relationships were assessed by using partial least squares structural equation modeling (PLS-SEM). To measure implicit information processing, a single category implicit association test was applied.

By applying the storytelling technique with parallax scrolling, the online shop increased visitors' UX on explicit and implicit information processing levels and increased the online shop's overall perceived attractiveness. Storytelling with parallax motion enables an efficient transmission of brand-related associations to consumers' minds, enhances their explicit and implicit brand attitudes and increases their willingness to pay a higher price. Moreover, this study provides empirical evidence on the effects of UX on brand-related measures by applying PLS-SEM and thus reveals a causal chain of effects from UX on online shop attractiveness, brand attitude and behavioral intentions. Again, explicit and implicit perceptions were considered.

Science and practice are increasingly emphasizing that storytelling emotionalizes content, which facilitates effective communication and builds strong relationships with customers. Little evidence exists about its efficient implementation in an online shopping context and in fulfilling hedonic and pragmatic needs throughout the online journey. This study provides novel insights into managing online shoppers' UX, brand-related perceptions and behavioral intentions with the optimal use of techniques to implement storytelling. Furthermore, this is one of the first studies to holistically consider the human perception of online shops by drawing on theories and methods of psychology, marketing, consumer behavior, brand research and consumer neuroscience and considering explicit and implicit information processing in terms of hedonic and pragmatic UX and brand-related measures.

The author identifies the traits of consumer resilience in emerging markets, classifies these major traits into five categories and analyses the influence relationships among them with distinctive focus on the psychological and personal resilience aspects.

The influence relations among the traits of consumer resilience from an expert perspective were identified with typical focus on electronic supply chains, and later the same was analysed through an intelligent influence modelling method, the grey causal modelling (GCM).

The major traits were analysed using the GCM, where the cause–consequence relations were observed for various objectives and the situational effects are noted. By constructing a magnitude plot and further a causal magnitude table, the important influence traits of consumer resilience for the considered case were observed and the same were auxiliary validated using an interpretive structural modelling (ISM) based approach.

As perceived from the results, it is evident that social support and recommendations from customers emerge as the principal influence traits of consumer resilience from an expert perspective, considering the case. The study can be further extended empirically to validate the findings.

Altogether, the author can recommend for practitioners that the influence of family, society, friends, peers as well as ratings from the customers can determine the level of consumer resilience. Hence, practitioners of customer relationship management can focus on improving the product and brand awareness among customers, so that more customers may recommend for typical products.

Consumer resilience depend on several factors, where the author has identified 25 major traits of the same and classified them into five major categories, including individual psychological factors, individual attitudes, individual socio demographic factors, micro environmental factors and macro environmental factors and the influence relations among them were studied from an expert perspective.

The study aims to identify the possible risk factors for electricity grids operational disruptions and to determine the most critical and influential risk indicators.

A multi-criteria decision-making best-worst method (BWM) is employed to quantitatively identify the most critical risk factors. The grey causal modeling (GCM) technique is employed to identify the causal and consequence factors and to effectively quantify them. The data used in this study consisted of two types – quantitative periodical data of critical factors taken from their respective government departments (e.g. Indian Meteorological Department, The Central Water Commission etc.) and the expert responses collected from professionals working in the Indian electric power sector.

The results of analysis for a case application in the Indian context shows that temperature dominates as the critical risk factor for electrical power grids, followed by humidity and crop production.

The study helps to understand the contribution of factors in electricity grids operational disruptions. Considering the cause consequences from the GCM causal analysis, rainfall, temperature and dam water levels are identified as the causal factors, while the crop production, stock prices, commodity prices are classified as the consequence factors. In practice, these causal factors can be controlled to reduce the overall effects.

From the results of the analysis, managers can use these outputs and compare the risk factors in electrical power grids for prioritization and subsequent considerations. It can assist the managers in efficient allocation of funds and manpower for building safeguards and creating risk management protocols based on the severity of the critical factor.

The research comprehensively analyses the risk factors of electrical power grids in India. Moreover, the study apprehends the cause-consequence pair of factors, which are having the maximum effect. Previous studies have been focused on identification of risk factors and preliminary analysis of their criticality using autoregression. This research paper takes it forward by using decision-making methods and causal analysis of the risk factors with blend of quantitative and expert response based data analysis to focus on the determination of the criticality of the risk factors for the Indian electric power grid.

This chapter reports on a rapidly growing trend in data analysis – analytic comparisons between baseline models and explanatory models. Baseline models estimate values for the dependent variable in the absence of hypothesized causal effects. Thus, the baseline models discussed in this chapter differ from the baseline models commonly used in sequential regression analyses.Baseline modelling entails iteration: (1) Researchers develop baseline models to capture key patterns in the empirical data that are independent of the hypothesized effects. (2) They compare these patterns with the patterns implied by their explanatory models. (3) They use the derived insights to improve their explanatory models. (4) They iterate by comparing their improved explanatory models with modified baseline models.The chapter draws on methodological literature in economics, applied psychology, and the philosophy of science to point out fundamental features of baseline modelling. Examples come from research in international business and management, emerging market economies and developing countries.Baseline modelling offers substantial advantages for theory development. Although analytic comparisons with baseline models originated in some research fields as early as the 1960s, they have not been widely discussed or applied in international management. Baseline modelling takes a more inductive and iterative approach to modelling and theory development. Because baseline modelling holds substantial potential, international-management scholars should explore its opportunities for advancing scientific progress.

One crucial but sometimes overlooked fact regarding the difference between observation in the cross-section and observation over time must be stated before proceeding further. Tempting though it is to draw conclusions about the dynamics of a process from cross-sectional observations taken as a snapshot of that process, it is a fallacious practice except under a very precise condition that is highly unlikely to obtain in processes of interest to the social scientist. That condition is known as ergodicity.

This study aims to analyse the effect of gun-related violence on housing values, controlling for the area's crime levels and locational factors. Previous studies that aimed to find a causal connection between crime and housing values used instrument variables to solve the endogeneity problem. Here, the authors have instead been able to take advantage of the fact that shootings have occurred in random time and space. This has made it possible to estimate models to create windows around the shooting (event) and to estimate the causal effects of the shootings. Thus, the authors aim to contribute to the regression discontinuity design method in this context to estimate the short-term effects.

Using the regression discontinuity design method, the authors can estimate the short-term effects of shootings.

Findings from the analysis indicate that shootings directly affect those who are impacted by shootings and indirectly affect the environments where shootings occur. The indirect effect of shootings is momentary as it is capitalised directly in housing values in the immediate area. The effect also appears to be relatively long-term and persistent as housing values have not returned to the price level before the shooting 100–200 days after the shooting. The capitalisation effect is higher the closer one gets to the central parts of the city. On the other hand, the capitalisation effect is not higher or lower in areas with a higher crime rate per capita.

The article contributes to the previous literature in several ways. First and foremost, it provides an explicit analysis of shootings in built-up areas and their hypothesised effect on property prices through the impact on attractiveness and perceived safety. As far as the authors know, no study has analysed this issue on the international level or in Sweden. In this way, the authors aim to develop a study that can provide critical knowledge about one of the adverse effects of shootings. The authors also contribute to the literature by utilising unique data material, which allows the authors to merge information from the police about the exact location of shootings in the Stockholm area with data on sales of apartments in the same residential areas. In addition to the exact location of the shootings (coordinates), the authors also have access to data about whether the shootings led to injuries or deaths. Thus, the authors have separated the effect of shootings and fatal shootings, which has not been done before. Finally, the authors set out to highlight the results as a contribution to the debate on shootings.

The purpose of this paper is to examine the effect of workfare programme participation on self-efficacy, because many studies suggest that sufficient self-efficacy is essential for successful job search in modern labour markets.

The paper analyses an exemplary German workfare programme’ the so-called “One-Euro-Jobs” programme and examines whether participation in this programme improved the self-efficacy of participants. The analyses are based on survey data (Panel Study Labour Market and Social Security) that were combined with administrative records of the Statistics Department of the German Federal Employment Agency to obtain more reliable information on programme participation. To detect causal effects of participation, the authors apply propensity score matching.

The findings show that participants’ self-efficacy, on average, was not improved by programme participation. Also, no well-determined positive effects of programme participation were found when controlling for the individual baseline level of self-efficacy.

The findings suggest that workfare programme participation did not fulfil several of the psychological functions of work necessary to enhance participants’ self-efficacy. The authors suggest a two-step approach to enhancing individuals’ self-efficacy and their job-search abilities: in the first step, workfare participation aims to improve employability; in the second step, participants can learn the extent to which they have become ready to work in a regular subsidised job.

Various studies examine the effect of workfare programme participation on employment prospects, well-being, health or social participation. Within the discourse on active labour market policy, this paper is the first to study the effect of workfare programme participation on self-efficacy.

Previous research suggests the crucial role of parents in developing social behaviors of their children. However, less evidence is available on the role of parents in shaping responsible financial management behavior among children for their later life. This study bridges this gap by investigating the role of financial parenting in improving well-being among young Saudi people. Particularly, this study examines the role of financial parenting, childhood financial socialization and childhood financial experiences in developing responsible financial self-efficacy and financial coping behaviors to determine financial well-being among young adults in Saudi Arabia.

This study uses a two-step mixed-method approach comprising analyses of symmetric (net effects) and asymmetric (combinatory effects) modelling to test the proposed model. A symmetrical analysis examines the role of financial parenting factors that are sufficient for improving financial well-being among Saudis. An asymmetrical analysis is used to explore that a set of combinations of financial parenting conditions lead to high performance of financial well-being. Data have been collected from 350 students enrolled in undergraduate and postgraduate programs in Saudi Arabia.

According to asymmetric modeling (i.e. fsQCA) analysis, parents and practitioners can combine financial parenting, childhood financial socialization and childhood financial experiences along with financial self-efficacy and financial coping behaviors in a way that satisfied the conditions (i.e. causal antecedent conditions) leading to high financial well-being. Importantly, the condition of high financial well-being is not mirror opposite of causal antecedent conditions of low financial well-being.

This study contributes to the current knowledge by applying both symmetrical and asymmetrical modelling to indicate a high level of financial well-being. Besides, there is sparse empirical evidence available in the context of Saudi Arabia on how financial parenting, socialization and financial experiences in childhood improve children's financial well-being in their later life.

According to asymmetric modeling (i.e. fsQCA) analysis, parents and practitioners can combine financial parenting, childhood financial socialization and childhood financial experiences along with financial self-efficacy and financial coping behaviors in a way that satisfied the conditions (i.e. causal antecedent conditions) leading to high financial well-being. Importantly, the condition of high financial well-being is not mirror opposite of causal antecedent conditions of low financial well-being. The parents and practitioners must be cautious to regulate the condition in which the combination of the antecedents is not in line with the causal recipes of financial well-being negation.

This study deepens the current knowledge by employing both symmetrical and asymmetrical analysis for testing structural and configurational models indicating the high performance of financial well-being . The study proposes and tests an integrated model to bring new contributions to prior literature. This study also attempts to propose valuable research directions for future researchers interested in the topic.

Researchers in management regularly face modelling issues that involve double-moderated mediation models. Here, the author illustrates how to conceptualise, specify and empirically estimate mediation effects when having to simultaneously account for continuous (Likert type) and nominal (i.e. group) moderator variables. Researchers’ estimates of the mediation effects suffer serious bias because of the effects of unaccounted confounders. This is an issue that plagues management research, and this study aims to show how to address these valid reservations for its focus models. In aiming to inform a wider management audience, the study deliberately uses the rich context of a focus case as this allows the author to clarify the nuances that management researchers face applying double-moderated mediation models. Specifically, the study’s focus case is on professionals’ willingness to implement a new government policy. The study also combines traditional and Bayesian statistical approaches and explains the differences in estimation and interpretation that are associated with the Bayesian approach. Explaining, and exemplifying the use of, the models, the author focuses on how one can substantially increase the robustness of the methods used in management research and can considerably improve the quality of the generated theoretical insights. The study also clarifies important assumptions and solutions.

The study uses a doubled moderated mediation Bayesian approach, and draws the sample data from a population of 5,199 professionals, all members of either the Dutch Association of Psychologists or the Dutch Association for Psychiatry. The data collection process resulted in 1,307 questionnaires being returned, a response rate of 25 per cent. All the items were measured using a Likert scale, ranging from “strongly disagree” to “strongly agree”, unless stated otherwise.

Explaining, and exemplifying the use of, the models the study focuses on how one can substantially increase the robustness of the methods used in management research and can considerably improve the quality of the generated theoretical insights.

This is an original approach exemplified for wider use by management researchers.

The purpose of this paper is to explore the existing mechanism through which business group affiliated firms in emerging markets (EMs) continue to generate superior performance.

The authors build our argument on the basis of how business group affiliation in EM facilitates internationalization and investment into innovation in affiliated firms compared to un-affiliated firm, resulting in higher firm performance. The authors use advance statistical modeling – causal mediation analysis to separate direct effect and indirect effect of business group affiliation in EM on performance through internationalization and investment into innovation of business group affiliated firms as mediating variables.

Based on 122,479 observations (firm year) from 17,235 Indian business group affiliated and un-affiliated firms, the findings help to identify that internationalization and investment into innovation of business group affiliated firms do have a mediating role in affiliation–performance relationship for EM business groups.

This study unravels the existing causal chain between business group affiliation in EMs and subsequent performance of affiliated firms. The authors complement institutional argument for superior performance of business group affiliation and focus on the performance implication of mediating strategic decisions in affiliated firms.