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1 – 10 of 13Carla Ramos, Adriana Bruscato Bortoluzzo and Danny P. Claro
This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer…
Abstract
Purpose
This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.
Design/methodology/approach
This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.
Findings
This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.
Research limitations/implications
The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.
Practical implications
This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.
Originality/value
This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.
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This study aims to investigate the impact of terrorism on financial inclusion that is achieved through automated teller machine penetration and bank branch expansion.
Abstract
Purpose
This study aims to investigate the impact of terrorism on financial inclusion that is achieved through automated teller machine penetration and bank branch expansion.
Design/methodology/approach
Eight countries that are the most terrorized countries in the world were analysed using the panel fixed effect regression model and the generalized linear model.
Findings
The results provide evidence that terrorism reduces the level of financial inclusion in countries experiencing terrorism, but the presence of strong legal institutions, accountability governance institutions and political stability governance institutions mitigate the adverse effect of terrorism on financial inclusion.
Originality/value
A growing literature has shown that terrorism affects the economy, yet little is known about its impact on financial inclusion.
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This study aims to examine the effect of gender equality on financial stability and financial inclusion for 14 developing countries using yearly data from 2005 to 2021.
Abstract
Purpose
This study aims to examine the effect of gender equality on financial stability and financial inclusion for 14 developing countries using yearly data from 2005 to 2021.
Design/methodology/approach
The two-stage least squares regression estimation and the generalized linear model regression estimation were used to investigate the effect of gender equality on financial stability and financial inclusion.
Findings
Gender equality has a significant positive effect on financial stability and financial inclusion in developing countries. Gender equality has a significant positive effect on financial stability and financial inclusion in African countries. Gender equality has a significant positive effect on financial stability but not on financial inclusion in non-African countries.
Originality/value
Little attention has been paid to the role of gender equality in promoting financial stability and financial inclusion. The authors address this issue in this study.
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Gaston Ares, Florencia Alcaire, Vanessa Gugliucci, Leandro Machín, Carolina de León, Virginia Natero and Tobias Otterbring
The current research aimed to examine the prevalence of Instagram posts featuring ultra-processed products targeted at adolescents in Uruguay and hence investigate the frequency…
Abstract
Purpose
The current research aimed to examine the prevalence of Instagram posts featuring ultra-processed products targeted at adolescents in Uruguay and hence investigate the frequency of such posts among a vulnerable consumer segment in a country that cannot be classified as WEIRD (i.e. Western, educated, industrialized, rich and democratic).
Design/methodology/approach
The study relied on a cross-sectional content analysis. A total of 2,014 Instagram posts promoting ultraprocessed products or brands commercializing such products, generated by 118 Instagram accounts between August 15th, 2020, and February 15th, 2021, were analyzed. Nine indicators of food marketing targeted at adolescents were selected to identify posts targeted at this age segment. Inductive coding was used to describe the content of the posts. Descriptive statistics and generalized linear models were used to analyze the data.
Findings
In total, 17.6% of the posts were identified as targeted at adolescents. Graphic design and adolescent language were the most prevalent indicators of marketing targeted at adolescents, followed by explicit references to adolescents or young adults and memes. Posts identified as targeted at adolescents mainly promoted snacks and discretionary foods. Differences in the content of posts identified as targeted and not targeted at adolescents were observed.
Research limitations/implications
The analysis was restricted to one social media platform in one country during a limited period of time, which limits the generalizability of the findings to other media platforms, samples and settings.
Social implications
Results stress the need to implement digital food marketing regulations to reduce exposure of adolescents to the deleterious effects of stemming from marketing of unhealthy foods and provide empirical evidence to inform their development.
Originality/value
The study breaks new ground by analyzing the prevalence and exploring the characteristics and content of Instagram posts promoting ultra-processed products to adolescents in an under-researched geographic area of the world.
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Jitendra Yadav, Kuldeep Singh, Nripendra P. Rana and Denis Dennehy
Social media has played a pivotal role in polarizing views on Russia–Ukraine conflict. The effects of polarization in online interactions have been extensively studied in many…
Abstract
Purpose
Social media has played a pivotal role in polarizing views on Russia–Ukraine conflict. The effects of polarization in online interactions have been extensively studied in many contexts. This research aims to examine how multiple social media sources may act as an integrator of information and act as a platform for depolarizing behaviors.
Design/methodology/approach
This study analyzes the communications of 6,662 tweets related to the sanctions imposed on Russia by using textual analytics and predictive modeling.
Findings
The research findings reveal that the tweeting behavior of netizens was depolarized because of information from multiple social media sources. However, the influx of information from non-organizational sources such as trending topics and discussions has a depolarizing impact on the user’s pre-established attitude.
Research limitations/implications
For policymakers, conflict mediators and observers, and members of society in general, there is a need for (1) continuous and consistent communication throughout the crisis, (2) transparency in the information being communicated and (3) public awareness of the polarized and conflicting information being provided from multiple actors that may be biased in the claims being made about the conflict crisis.
Originality/value
While previous research has examined Russia–Ukraine conflict from a variety of perspectives, this is the first study to examine how social media might be used to reduce attitude polarization during times of conflict.
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Bülent Doğan, Yavuz Selim Balcioglu and Meral Elçi
This study aims to elucidate the dynamics of social media discourse during global health events, specifically investigating how users across different platforms perceive, react to…
Abstract
Purpose
This study aims to elucidate the dynamics of social media discourse during global health events, specifically investigating how users across different platforms perceive, react to and engage with information concerning such crises.
Design/methodology/approach
A mixed-method approach was employed, combining both quantitative and qualitative data collection. Initially, thematic analysis was applied to a data set of social media posts across four major platforms over a 12-month period. This was followed by sentiment analysis to discern the predominant emotions embedded within these communications. Statistical tools were used to validate findings, ensuring robustness in the results.
Findings
The results showcased discernible thematic and emotional disparities across platforms. While some platforms leaned toward factual information dissemination, others were rife with user sentiments, anecdotes and personal experiences. Overall, a global sense of concern was evident, but the ways in which this concern manifested varied significantly between platforms.
Research limitations/implications
The primary limitation is the potential non-representativeness of the sample, as only four major social media platforms were considered. Future studies might expand the scope to include emerging platforms or non-English language platforms. Additionally, the rapidly evolving nature of social media discourse implies that findings might be time-bound, necessitating periodic follow-up studies.
Practical implications
Understanding the nature of discourse on various platforms can guide health organizations, policymakers and communicators in tailoring their messages. Recognizing where factual information is required, versus where sentiment and personal stories resonate, can enhance the efficacy of public health communication strategies.
Social implications
The study underscores the societal reliance on social media for information during crises. Recognizing the different ways in which communities engage with, and are influenced by, platform-specific discourse can help in fostering a more informed and empathetic society, better equipped to handle global challenges.
Originality/value
This research is among the first to offer a comprehensive, cross-platform analysis of social media discourse during a global health event. By comparing user engagement across platforms, it provides unique insights into the multifaceted nature of public sentiment and information dissemination during crises.
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Junping Qiu, Qinze Mi, Zhongyang Xu, Tingyong Zhang and Tao Zhou
Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to…
Abstract
Purpose
Based on the social interaction theory and trust theory, this study investigates the switching of users on social question and answer (Q&A) platforms from knowledge seekers to knowledge contributors.
Design/methodology/approach
We used Python to gather data from Zhihu, performed hypothesis testing on the models using Poisson regression and finally conducted a mediation effect analysis.
Findings
The findings reveal that knowledge seeking impacts users' motivation for information interaction, emotional interaction and trust. Notably, information interaction and trust exhibit a chained mediation effect that subsequently influences knowledge contribution.
Originality/value
Current studies on user knowledge behavior typically examine individual actions, rarely connecting knowledge seeking and knowledge contribution. However, the balance of knowledge inflow and outflow is crucial for social Q&A platforms. To cover this gap, this paper empirically investigates the switching between knowledge seeking and knowledge contribution based on the social interaction theory and trust theory.
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Jingqi Zhang, Shaohua Jiang and Xiaomin Qi
The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the…
Abstract
Purpose
The purpose of this paper is to conduct a comprehensive study on building, fire and evacuation, so as to effectively improve the efficiency of building fire evacuation and the management level of fire evacuation site. Make up for the difficulties of BIM technology in effectively connecting building information and fire data.
Design/methodology/approach
First, this paper establishes a fire model and an evacuation model based on BIM information. Then, the safety index (SI) is introduced as a comprehensive index, and the IRI is established by integrating the SI function to evaluate the safety of evacuation routes. Based on these two indices, the IRI-based fire evacuation model is established.
Findings
This study offers an Improved Risk Index (IRI)-based fire evacuation model, which may achieve effective evacuation in fire scenes. And the model is verified by taking the fire evacuation of a shopping center building as an example.
Originality/value
This paper proposes a fire evacuation principle based on IRI, so that the relevant personnel can comprehensively consider the fire factors and evacuation factors to achieve the optimization of building design, thereby improving the fire safety of buildings.
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Jason Scott Entsminger and Lucy McGowan
This paper aims to investigate associations between firm resources and reliance on entrepreneurial marketing (EM) channels among agrofood ventures. It accounts for agropreneur…
Abstract
Purpose
This paper aims to investigate associations between firm resources and reliance on entrepreneurial marketing (EM) channels among agrofood ventures. It accounts for agropreneur gender and racial/ethnic status in the context of marketing channel portfolio composition. The authors examine the established assumption that resource limitations drive EM and whether socially disadvantaged status of agropreneurs is associated with marketing strategy beyond standard resourcing measures.
Design/methodology/approach
Using 2015 Local Foods Marketing Practices Survey data, the authors apply linear regression to investigate differences in the use of EM channels, accounting for resources, social status and other factors.
Findings
Limited-resource ventures rely more on consumer-oriented channels that require EM practices. Socially disadvantaged entrepreneurs favor these channels, even when accounting for resources. Notably, ventures headed by men of color rely more on the most customer-centric local foods marketing channel.
Research limitations/implications
Future research should investigate how social and human capital influences the use of EM.
Practical implications
Entrepreneurial support policy and practice for agropreneurs should be cautious about the “double-burden” folk theorem of intersectional disadvantage and review how to best direct resources on EM to groups most likely to benefit.
Originality/value
This paper uses a unique, restricted, nation-wide, federal data set to examine relationships between resource endowments, social status and the composition of agrofood enterprises’ marketing channel portfolios. To the best of the authors’ knowledge, it is the first to include racial- and ethnic-minority status of agropreneurs and to account for intersectionality with gender.
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Gaurav Kumar, Molla Ramizur Rahman, Abhinav Rajverma and Arun Kumar Misra
This study aims to analyse the systemic risk emitted by all publicly listed commercial banks in a key emerging economy, India.
Abstract
Purpose
This study aims to analyse the systemic risk emitted by all publicly listed commercial banks in a key emerging economy, India.
Design/methodology/approach
The study makes use of the Tobias and Brunnermeier (2016) estimator to quantify the systemic risk (ΔCoVaR) that banks contribute to the system. The methodology addresses a classification problem based on the probability that a particular bank will emit high systemic risk or moderate systemic risk. The study applies machine learning models such as logistic regression, random forest (RF), neural networks and gradient boosting machine (GBM) and addresses the issue of imbalanced data sets to investigate bank’s balance sheet features and bank’s stock features which may potentially determine the factors of systemic risk emission.
Findings
The study reports that across various performance matrices, the authors find that two specifications are preferred: RF and GBM. The study identifies lag of the estimator of systemic risk, stock beta, stock volatility and return on equity as important features to explain emission of systemic risk.
Practical implications
The findings will help banks and regulators with the key features that can be used to formulate the policy decisions.
Originality/value
This study contributes to the existing literature by suggesting classification algorithms that can be used to model the probability of systemic risk emission in a classification problem setting. Further, the study identifies the features responsible for the likelihood of systemic risk.
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