Consumer Outcomes Research Articles

Corporate social responsibility activities, consumers’ trust and gender: an analysis of Islamic banks in Somalia

PurposeThe purpose of this study is to investigate the link between corporate social responsibility (CSR) and the amount of trust customers have in Somali Islamic banks. Furthermore, the role of gender in CSR activities and Islamic bank clientele is evaluated.Design/methodology/approachThroughout February and March 2022, 410 clients of Islamic banks in Somalia were surveyed using a questionnaire. The partial least squares approach and the structural equation model are applied to examine the data.FindingsFindings indicate that all variables of CSR activities, such as social product, social legal, social needs, social environment and social employees’ responsibility, are influential and significant predictors of trust in Islamic banks in Somalia. Gender inequalities moderate the relationship between social product, social needs, social environment, social employee and trust. Conversely, only social legal responsibility was unaffected by gender differences in Somalia regarding people’s trust in Islamic banks.Practical implicationsA sample from a developing country such as Somalia is useful for shedding light on the outcomes of consumers’ perceptions of and trust in businesses’ CSR in the developing world. Furthermore, this study contributes to knowledge regarding CSR and how it can help the Islamic banking industry. Its findings will be useful to policymakers and regulatory bodies in the banking industry in their efforts to improve CSR.Originality/valueTo the best of the authors’ knowledge, this study is the first empirical investigation of its kind about the understudied relationship among customer trust, CSR efforts and gender in Somalia context. Furthermore, it investigates how gender specifically moderates CSR in the Islamic banking sector in a developing country.

Community pharmacists' views and experiences of delivering in-pharmacy medication reviews for people living with severe and persistent mental illness: a qualitative study.

People living with severe and persistent mental illness (SPMI) often take multiple medications and are at risk of experiencing medication related problems. Medication review services have the potential to reduce inappropriate use of psychotropic medications and improve adherence. However, there is limited research regarding pharmacists' perspectives when providing such services. To explore community pharmacists' views and experiences of providing an in-pharmacy medication review (MedsCheck) for people living with SPMI. Semi-structured interviews were conducted between November 2021 and May 2022 with community pharmacists participating in the comparator group of the PharMIbridge Randomised Controlled Trial (RCT), which aimed to improve medication adherence and manage physical health concerns for people living with SPMI. Interviews were recorded, transcribed, and analysed using inductive thematic analysis. Fifteen semi-structured interviews were conducted with community pharmacists including pharmacy owners, managers and employee pharmacists. Most pharmacist participants who were interviewed (n = 10) were aged under 39 and more than half (n = 8) had 10 or more years of pharmacy experience. Five key themes were identified: 1) Pharmacists' roles in the management of SPMI in community pharmacy; 2) Mental health education and training; 3) Pharmacy resources; 4) Challenges with interprofessional collaboration and 5) Impact on professional relationships and consumer outcomes. Pharmacists are motivated to support people living with SPMI. Mental health training, as well as arrangements regarding pharmacy workflow and appropriate remuneration are needed to enable pharmacists to better support people living with SPMI. Referral pathways should be directly accessible by community pharmacists to assist interprofessional collaboration.

Accessing the TikTok Influencer Marketing on Consumer Behavior: An Econometric Examination

Background: This research aims to access the effect of TikTok influencer marketing on consumer behavior using econometric models. TikTok has emerged as a popular social media platform, with influencers playing a crucial role in molding consumer perspectives and purchasing decisions. However, there is a need to empirically understand the effectiveness of TikTok influencer collaborations in driving brand awareness, purchase intentions, and actual purchasing behavior. Methods: Data for this study is gathered through a survey that is conducted to TikTok users, capturing variables such as exposure to influencer collaborations, engagement with influencer content, brand recall, and trust in TikTok influencers. Demographic information (gender, age, income, education) are also collected. Econometric models, including regression and correlation analysis, are applied to examine the gathered data, and assess the relationship between TikTok influencer marketing and consumer behavior outcomes (brand awareness, purchase intentions, and actual purchasing behavior). Results: The outcomes of the econometric analysis offer valuable information into the influence of TikTok influencer marketing on consumer behavior. The research illuminates the efficacy of influencer collaborations in driving brand awareness among consumers. It also unveil the influence of TikTok influencer promotions on the inclinations of consumers to buy products or services. The findings will contribute to understanding the extent to which TikTok influencer marketing affects actual purchasing behavior. Contribution: This research addresses a research gap by investigating the influence of TikTok influencer collaborations on consumer behavior. Through an econometric analysis, it provides quantitative insights into the relationship between TikTok influencer marketing and consumer outcomes. The findings inform marketers and brands about evaluating the efficiency of TikTok influencer campaigns, aiding in the development of impactful marketing strategies. This research enhances our insights into the function of TikTok influencer marketing in molding consumer behavior and contributes to the field of social media marketing.
 
 Received: 22 October 2023 / Accepted: 28 February 2024 / Published: 5 March 2024

Evaluating outcomes following adolescent and youth mental health inpatient admissions: A systematic review.

Increasing rates of mental illness among young people, exacerbated by the negative impacts of COVID-19, has resulted in growing pressure on available psychiatric resources to meet increasing demand. Inpatient units provide specialist care for young people with the most severe and complex mental disorders but are one of the most expensive models of psychiatric care. The aim of this review is to provide an update on the effectiveness of adolescent and youth mental health inpatient units in improving outcomes to inform the most efficacious use of psychiatric resources. Systematic searches of PubMed, The Cochrane Library, PsycINFO, EMBASE, and Web of Science were conducted for studies published in English between January 2011 to May 2022. Criteria for selection included participants aged 12-25 years who had been admitted to amental health inpatient unit. Studies were excluded if set in substance abuse or disability specific units, outpatient or forensic settings, or assessed novel interventions. 23 studies were identified as meeting inclusion criteria, with most (n = 19) utilizing a pre-post observational design and reporting improvement across various domains following inpatient treatment. A total of 24 different outcome measures or methods were used meaning a meta-analysis of results was not possible. There was also a lack of consistency across models of care, lengths of stay, admission policies, and interventions provided. Inpatient units provide positive outcomes for consumers however a clear understanding of clinical significance and comparison to other treatment settings is lacking.

What does Covid-19 teach us about English contract law?

AbstractThis paper examines how English courts have responded to the contract problems generated by the Covid-19 pandemic and considers what this tells us about future contract law development. In relation to consumers, the case law on pandemic-affected contracts, though limited, indicates that traditional contract doctrine does not necessarily produce beneficial outcomes for consumers. This further diminishes the importance of the common law in the consumer contracting context. In the commercial sector, contracting parties were encouraged by government and other organisations to co-operate with one another and act in good faith during the crisis, but this has not influenced the courts applying contract law in the pandemic aftermath. The emerging case law suggests that contract law has retained its commitment to certainty, freedom of contract and sanctity of contract, notwithstanding the extraordinary circumstances around the outbreak and its unpredictable effects on contracts. The unalloyed application of formal contract law in the post-pandemic case law augments the position of relational norms as extra-contractual in English law, putting the further judicial development of relational contract principles in doubt. The paper concludes that despite the considerable social and economic upheaval caused by the pandemic, its impact on contract law development is likely to be minimal.

Identifying value chain trade-offs from fruit and vegetable aggregation services in Bangladesh using a system dynamics approach.

Significant progress has been made in cereal production in Bangladesh due to an agricultural policy environment that prioritizes the productivity of staple crops over fruit and vegetables (F&V). However, many smallholder farmers remain poorly connected to markets, which may lead to a limited supply response of F&V that can reduce opportunities for sufficient intake in neglected, consumer-facing, smaller retail markets. To address this issue, aggregation schemes have been conceived that collect and transport F&Vs on behalf of multiple farmers. Given the volume of horticultural produce produced and the reliance on developed transport infrastructure, aggregation schemes tend to supply wholesale and urban markets rather than underdeveloped rural and isolated markets. To this end, we investigated how a particular aggregation intervention ('Loop') could potentially improve the distribution of F&V to smaller markets whilst improving farmer benefits. We used an innovative system dynamics modeling approach based on Loop`s aggregation services in Jashore, Bangladesh, and to identify the potential trade-offs between consumer outcomes in retail markets and farmer benefits. We find that combining aggregation with a quota at the smaller market, transport subsidy, and current price growth does not result in trade-offs between consumer purchases and farmers`benefits. However, combining aggregation with current price growth can increase demand without losing farmers`benefits. The findings emphasize that standalone and multiple market-oriented interventions generate broader win-win benefits to promote inclusive food systems.

Artificial intelligence vs. autonomous decision-making in streaming platforms: A mixed-method approach

Although the empowerment of technology is of great value to society, little is known about its downstream effects on consumers' decisions. This research draws on the expectation–confirmation theory and autonomy in artificial intelligence (AI) and investigates how AI (vs. autonomous choice) has detrimental effects on consumer outcomes, creating an autonomy-technology tension — i.e., the conflict arising from AI technology diminishing consumers' autonomy in their choices. Four studies using a mixed-method approach reveal that the use of AI recommendations in streaming platforms creates an autonomy-technology tension that reduces consumers' performance expectancy, thus lowering their satisfaction. However, such effects are contingent on the nature of the AI recommendations. While a mismatch between AI recommendations and consumer preferences might backfire, AI's negative effect is mitigated when choices match consumers' preferences. We make significant theoretical and practical contributions to empirical research on consumers' sense of autonomy while interacting with AI.

Meme marketing effectiveness: A moderated-mediation model

Underpinned by brand placement literature, associative network theory, and narrative transportation theory, this research examines how meme marketing types (brand prominent and brand subtle) create immersive consumer experiences through narrative transportation and the moderating effects of consumer brand knowledge, meme literacy, and linguistic characteristics (i.e., pronouns) on meme marketing effectiveness. Study 1 (N = 300) confirms that brand prominent meme marketing generates more favourable consumer outcomes (attitude towards ad, customer engagement) and narrative transportation compared to brand subtle meme marketing. Additionally, Study 1 examines the moderating effects of consumer brand knowledge and the mediating role of narrative transportation. Study 2 (N = 300) validates the findings of Study 1 and assesses the mediating role of narrative transportation between brand prominent meme marketing (vs. brand subtle) and outcomes among consumers with varying meme literacy. Brand prominent meme marketing yields profound consumer outcomes and narrative transportation, especially with low brand knowledge. Study 3 (N = 253) confirms the results of Studies 1 and 2 and further introduces a novel linguistic moderator, examining the use of first-person and second-person pronouns within the meme marketing content using a different product category. This study uncovers the influence of second-person pronouns on intensifying narrative transportation. Empirical evidence supports all three moderated mediation models. Overall, this study adds to the knowledge on meme marketing and provides useful insights for designing and targeting effective meme marketing campaigns.

A Longitudinal Analysis of Trajectories and Predictors of Fidelity Using the SafeCare Parenting Model.

Evidence-based practice (EBP) fidelity, understood as the extent to which a program is implemented as the developers intended, is a key implementation variable which likely relates to consumer outcomes. However, studies that track fidelity longitudinally and at large scale are uncommon, and finding reliable predictors of fidelity has proven to be a complex challenge. Further, attitudes toward EBP are a potentially important predictor of fidelity, but results across the literature have been mixed. The purpose of the present study is to use data from the ongoing implementation and dissemination of the SafeCare model to better understand (1) the characteristics of SafeCare implementation fidelity trajectories, and (2) whether individual level factors predict differences in fidelity and fidelity trajectories, especially provider attitudes toward EBP. The analyses reported here include 14,778 observed fidelity sessions by 868 providers in 172 agencies. We use multilevel modeling to examine fidelity, fidelity trajectories over time, and several potential individual-level predictors of fidelity, including demographics, work history, and attitudes toward EBP. We found: (1) that SafeCare fidelity begins high at baseline (93.85% on average); (2) that SafeCare fidelity displays a statistically significant trend of positive linear growth, even among those with less positive attitudes; and (3) that positive attitudes are associated with slightly higher fidelity on average and at baseline, while negative attitudes are associated with slightly lower fidelity on average and at baseline. To our knowledge, this is the largest longitudinal analysis of EBP fidelity in a child welfare program to date, and our findings support the notion that intensive coaching supports which are titrated over time can be sufficient to ensure sustained high fidelity, at least in some cases. Further, these findings indicate that robust training and coaching processes can ensure high fidelity and fidelity growth even among providers with less positive attitudes toward EBP.

Barriers and enablers to implementing police mental health co-responder programs: A qualitative study using the consolidated framework for implementation research.

Police and mental health co-responder programs operate internationally and can be effective in providing timely and appropriate assessment, brief intervention, and referral services for people experiencing mental health crises. However, these models vary greatly, and little is known about how the design and implementation of these programs impacts their effectiveness. This study was a qualitative, post hoc implementation determinant evaluation of mental health co-responder units in Brisbane, Australia, comprising of verbal or written interviews with police and mental health staff with an on-road role in the co-responder units, and their managers. The Consolidated Framework for Implementation Research was used to identify barriers and enablers to the program's implementation and effectiveness. Participants (n = 30) from all groups felt strongly that the co-responder units are a substantial improvement over the usual police management of mental health crisis cases, and lead to better outcomes for consumers and the service. Enablers included an information-sharing agreement; the Mental Health Co-Responder (MHCORE) program's compatibility with existing police and mental health services; and the learning opportunity for both organizations. Barriers included cultural differences between the organizations, particularly risk-aversion to suicidality for police and a focus on least-restrictive practices for health; extensive documentation requirements for health; and a lack of specific mental health training for police. Using an evidence-based implementation science framework enabled identification of a broad range of contextual barriers and enablers to implementation of police mental health co-responder programs. Adapting the program to address these barriers and enablers during the planning, implementation, monitoring, and evaluation phases increases the likelihood of the service's effectiveness. These findings will inform the spread and scale of the co-responder program across Queensland, and will be relevant to police districts internationally considering implementing a co-responder program.

Navigating online health information: Insights into consumer influence and decision-making strategies-An overview of reviews.

Communities' use of technology and the internet for online health information (OHI) is increasing exponentially. An understanding of how and why individuals access OHI, and how this information influences decisions on health, medicines and self-care practices is critical. This review aims to: (1) identify the factors influencing OHI-seeking behaviour; (2) evaluate the evidence of OHI on self-care practices; and (3) outline strategies to improve online informed decision-making and assess the impact of these strategies on consumer outcomes. A review of systematic reviews was conducted in November of 2023, following the Cochrane Handbook and PRISMA guidelines, and using PubMed, Scopus, Web of Science and EBSCOhost databases. The methodological quality of retrieved reviews was appraised using the AMSTAR 2 tool. The search retrieved 1725 records. Of these, 943 were screened, and 33 were included in the final analysis. The most frequently identified reasons for seeking OHI were to retrieve diagnostic and treatment information, and well-being and emotional support. Level of education and socio-economic status influenced OHI-seeking. OHI directly influenced self-care decision-making by individuals and their relationships and communication with healthcare providers. Overall, OHI-seeking (and interventions to promote the use of OHI) enhanced individuals' confidence, skills and knowledge. The findings highlight the benefits of OHI-seeking and its potential influence on self-care decisions. Future research should focus on strategies that would promote the pursuit of high-quality, up-to-date OHI and on the development of interventions for healthcare professionals to improve patients' use of OHI in self-care and self-efficacy.

Industrial carbon capture utilisation and storage in the UK: The importance of wage responses in conditioning the outcomes of a new UK CO2 transport and storage industry emerging in a labour supply constrained economy

Carbon capture usage and storage (CCUS) is emerging as an important solution in delivering deep emissions reductions in energy-intensive industries, enabling hydrogen production, and possibly directly capturing existing carbon dioxide (CO2) from the atmosphere. The potential for associated new industry activity – for example in CO2 Transport and Storage (T&S) – could also be important in transitioning economies with legacy investment in oil and gas extraction. This paper addresses the question of how introducing a nascent T&S industry may impact the wider UK economy in the presence of persisting national labour supply constraints. It does so by refining a multi-sector economy-wide computable general equilibrium (CGE) model of the UK to run scenarios focussed on the emergence of a nascent sector, involving identification of benchmark activity – here, the existing oil and gas industry – where that nascent sector is not currently represented in national accounting data. Crucially, the CGE model embeds a theoretically and empirically tested wage bargaining function to consider how cost and price pressures triggered will condition dynamic outcomes for producers, consumers and government budgets. Results suggest that emergence of a new T&S industry is likely to deliver sustained net gains in UK employment and GDP. However, maximising T&S-linked jobs gains while minimising displacement of employment and price pressures elsewhere in the economy requires policy action to alleviate labour supply and skills constraints. This reinforces policy and industry recommendations around the need for net zero workforce planning and attention to the potential fiscal implications of taking action, or not/in different timeframes.

Berry Consumption and Sleep in the Adult US General Population: Results from the National Health and Nutrition Examination Survey 2005-2018.

Poor sleep is associated with numerous adverse health outcomes. Berries are rich in micronutrients and antioxidants that may improve sleep quality and duration. We determined the association of berry consumption and sleep duration and sleep difficulty among adult participants in NHANES. We analyzed the diet of US adults aged ≥ 20 y using two non-consecutive 24 h recalls from the National Health and Nutrition Examination Survey 2005 to 2018 (N = 29,217). Poor sleep quality was measured by sleep duration (short sleep duration: <7 h), long sleep (≥9 h), and reported sleep difficulty. The relative risk of poor sleep outcomes for berry consumers vs. nonconsumers was modelled using population weight-adjusted multivariable general logistic regression. About 46% of participants reported inadequate sleep duration, and 27% reported sleep difficulties. Twenty-two percent reported consuming berries. Berry consumers had a 10-17% decreased risk of short sleep. The findings were consistent for specific berry types including strawberries and blueberries (p < 0.05). No significant associations with long sleep were found for total berries and any berry types. A decreased risk of sleep difficulties was found to be linked to blackberry consumption (adjusted OR = 0.63, 95% CI: 0.40-0.97; p = 0.036) but not for other berries. US adult berry consumers had a decreased risk of reporting short sleep compared to nonconsumers. Berries are underconsumed foods in the US adult population, and increased berry consumption may improve sleep quality.

The risks of a form-based approach to exclusionary abuses of dominance – an economic perspective

The European Commission has initiated the process of changing how exclusionary abuses of dominance are evaluated, moving towards a more ‘form-based’ approach compared to the current ‘effects-based’ approach. This article explains that, if not implemented correctly, its planned approach risks worsening consumer outcomes. This article outlines the Commission’s existing approach to taking enforcement action against exclusionary abuses, and the two actions taken by the Commission to develop this approach. Then, it explores three cases where the false positives that arise from a form-based approach, rather than an effects-based approach, risk worsening outcomes for consumers. It suggests that, while an effects-based approach has its limitations, the Commission should ensure that it does not err too far into adopting a completely form-based approach as it develops updated rules on exclusionary abuses.

AI credibility and consumer-AI experiences: a conceptual framework

PurposeThis study aims to conceptualize the relationship of perceived artificial intelligence (AI) credibility with consumer-AI experiences. With the widespread deployment of AI in marketing and services, consumer-AI experiences are common and an emerging research area in marketing. Various factors affecting consumer-AI experiences have been studied, but one crucial factor – perceived AI credibility is relatively underexplored which the authors aim to envision and conceptualize.Design/methodology/approachThis study employs a conceptual development approach to propose relationships among constructs, supported by 34 semi-structured consumer interviews.FindingsThis study defines AI credibility using source credibility theory (SCT). The conceptual framework of this study shows how perceived AI credibility positively affects four consumer-AI experiences: (1) data capture, (2) classification, (3) delegation, and (4) social interaction. Perceived justice is proposed to mediate this effect. Improved consumer-AI experiences can elicit favorable consumer outcomes toward AI-enabled offerings, such as the intention to share data, follow recommendations, delegate tasks, and interact more. Individual and contextual moderators limit the positive effect of perceived AI credibility on consumer-AI experiences.Research limitations/implicationsThis study contributes to the emerging research on AI credibility and consumer-AI experiences that may improve consumer-AI experiences. This study offers a comprehensive model with consequences, mechanism, and moderators to guide future research.Practical implicationsThe authors guide marketers with ways to improve the four consumer-AI experiences by enhancing consumers' perceived AI credibility.Originality/valueThis study uses SCT to define AI credibility and takes a justice theory perspective to develop the conceptual framework.

Optimizing day-ahead energy management with demand response in a PV-diesel-battery system using a hybrid GOA-SNN strategy

This manuscript presents a hybrid technique for the day-ahead energy management strategy of hybrid renewable energy systems (HRES) integrated with demand response (DR). The HRES consists of Photovoltaic (PV), Diesel Generator (DG), and battery systems. The proposed method, named GOA-SNN strategy, combines the Gazelle Optimization algorithm (GOA) and spiking neural network (SNN) to improve outcomes for consumers and utility providers. The objective is to minimize human intervention and leverage advanced bi-directional communication. The focus of this study is on off-grid systems. The proposed strategy determines optimal incentives and power commands to maximize the operation of the HRES within a 24-hour control horizon. The GOA is used to optimize the scheduling of energy resources, considering constraints such as energy demand, battery state of charge, and grid availability. The SNN is used to predict energy demand using historical data and external factors. The strategy utilizes lower electricity prices to influence consumer behavior and identifies the ideal time periods to offer these discounted prices, optimizing the expected benefits of energy management. The proposed technique's performance is evaluated through MATLAB or Simulink simulations and compared against existing methods. The results demonstrate that the GOA-SNN strategy achieves cost savings and reduces computation time, making it an efficient and effective solution for energy management in hybrid renewable energy systems. The existing approach like BSSA, NPO, OSA and proposed technique accuracy becomes 70.23%, 75.59%, 89.42% and 95.21%. From this analysis, it concludes that the proposed method based accuracy is high compared with existing techniques.

Predictive Analysis of Sales Using the Apriori Algorithm: A Comprehensive Study on Sales Forecasting and Business Strategies in the Retail Industry.

In the digital age, businesses are increasingly leveraging the internet as a pivotal platform for expansion. Establishing an online presence, whether through official websites or e-commerce platforms, has become imperative. Within this landscape, the integration of data mining technology has introduced innovative predictive techniques, revolutionizing the relationship between customers and businesses. Entrepreneurs are driven to curate their products systematically, aligning them with patterns derived from extensive data analyses, including user ratings, behavior, and purchasing history. Such analyses hold the key to predicting consumer outcomes, shaping strategies that resonate with customer preferences. In this context, the Apriori algorithm emerges as a beacon of insight and prediction. By identifying frequent itemsets—sets of items that meet specific support and confidence thresholds—Apriori empowers businesses to discern meaningful patterns in customer preferences. Support quantifies the frequency of specific items, while confidence illuminates sequential product acquisition behaviors. These insights are invaluable in attracting and retaining customers. Notably, the Apriori algorithm transcends traditional sales prediction paradigms. Its versatility extends beyond commerce, finding applications in diverse domains such as weather forecasting, disease prediction, and intrusion detection. This paper adopts a quantitative method and delves into the strategic application of the Apriori algorithm, specifically in the realm of sales forecasting.

The role of augmented reality in shaping purchase intentions and WOM for luxury products

The literature examining the influence of augmented reality (AR)-driven experiences on consumer outcomes in retail is at an emerging stage, with little investigation conducted in the context of luxury products. Leveraging the affect-as-information theory and the stimulus-organism–response framework, this study examines the influence of AR-driven application experience for luxury brands on consumers’ affective responses (flow, emotional involvement, and pleasure), and cognitive responses (trust and experience satisfaction). These, in turn, enhance behavioural responses, in the form of purchase intention and word of mouth. The effects are tested for products with different levels of tactile input requirement. The current study sensitizes luxury brands about the important role of AR-based applications in driving product sales and the emergence of modern technologies as part of omnichannel strategies.

Understanding the impact of fashion app emotional attachment on consumer responses: the role of e-servicescape, customer experience and perceived value of online shopping

PurposeThe primary purpose of this study is to examine the relationship between conumers' emotional attachment towards fashion apps and positive behavioral outcomes, such as e-WoM and repurchase intention. The study also aims to explore how e-servicescape, customer experience and perceived value of online shopping influence this relationships.Design/methodology/approachThe study has used quantitative research methods to collect data from a sample of 484 consumers who had previous experience of purchasing using fashion apps. Data were collected from university students enrolled in university in Gujarat, India using an online self-administered questionnaire. The data are analyzed using structure equation modeling to determine the relationships between the variables under investigation.FindingsThe results demonstrate relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM. The study found support for hypotheses 1, 2 and 3, highlighting the influence of e-servicescape, customer experience and perceived value of online shopping in developing emotional attachment with fashion apps. The study also confirmed hypotheses 5 and 6, which suggest that consumers who have a stronger emotional attachment to fashion apps are more likely to intend to repurchase fashion products and engage in positive electronic word-of-mouth behavior for fashion brands.Originality/valueIn today's digital age, fashion apps are vital for fashion retailers to remain competitive and offer their customers a smooth and immersive shopping experience . Given the potential impact of fashion apps on the customer behavior, it is essential to investigate the relationship relationships between e-servicescape, customer experience and perceived value of online shopping, emotional attachment and the two consumer outcomes: repurchase intention and e-WoM in the context of fashion apps. The findings of the study are expected to contribute to the understanding of consumer behavior in the context of fashion apps and e-commerce more broadly. The results may also provide insights into how fashion retailers can improve their online presence and customer experiences to increase emotional attachment and positive behavioral outcomes.Practical implicationsThe results of this study have several implications for online retail managers and fashion app developers. The study provides strong support for the idea that the extent to which online customers feel emotionally attached to fashion apps is strongly related to their e-WoM and repurchase intention. Moreover, the results of the study suggest that online retailers who are looking to cultivate emotional connections with consumers through fashion apps should prioritize three key areas: e-servicescape, customer experience and perceived value of online shopping.

An integrated model predicting the drivers of mobile payment outcomes: evidence from emerging markets

PurposeBecause the success of m-payment services depends on the enablers and barriers that affect user satisfaction, the present research explores the effects of perceived value and sacrifices on users' satisfaction with m-payment services. The predicted relationships among perceived value, perceived sacrifices, users' satisfaction, continuance intention, word-of-mouth (WOM), shopping effectiveness, quality of life (QOL) and stickiness were established based on the mobile technology acceptance model (MTAM) and the value-based adoption model (VAM).Design/methodology/approachA representative data sample of 430 Egyptian banking clients was analyzed to test the hypotheses using partial least squares-structural equation modeling (PLS-SEM).FindingsThe findings revealed that all perceived value constructs significantly positively affect users' satisfaction. Moreover, all perceived sacrifice constructs significantly negatively affect users' satisfaction. Users' satisfaction, in turn, has a significant positive effect on continuance intention, WOM, shopping effectiveness, QOL and stickiness with m-payment services.Originality/valueThis is the first study to examine several levels of m-payment outcomes, including m-payment, consumer and bank outcomes, based on the integration of MTAM and VAM models.