Search results

This research aims to examine the factors that influence customers' product return intentions and proposes that YouTube product reviews can mitigate customers' desire to return a product.

The proposed theoretical research model and hypothesized relationship were investigated using a quantitative process. This study used 302 data from Indonesian young adult respondents to examine the structural model, which was analyzed using the SmartPLS 3.2 software package.

The results show that YouTube product reviews, product fit uncertainty and customer satisfaction are the key determinants of customers' product return intention. Furthermore, the results show that the credibility of YouTube product reviews has a major impact on customers' familiarity with a product, satisfaction and the likelihood of returning goods to sellers.

In the e-commerce industry, increasing the use of YouTube product reviews will help businesses eliminate unnecessary product returns. Sellers are also encouraged to collaborate with YouTube producers to review specific products, which can benefit companies by raising brand awareness and gaining customer feedback. Furthermore, YouTube online product reviews can help consumers avoid having an unpleasant shopping experience that causes emotional reactions and lowers satisfaction.

Most research has not considered antecedents in observing the product return phenomenon; this study observes a prerequisite of consumer product returns (i.e. information asymmetry and product familiarity) and investigates the relationships between YouTube product reviews, customer satisfaction and product return intention.

Motivated by the real-world practice that the boom of the online selling induces a higher product return as well, selecting which online channel mode indicates who takes ownership over the product and thus bears the loss of the product return. This paper aims to seek the optimal online channel modes for the two members in a platform supply chain in the presence of product returns.

This study aims to develop a platform supply chain that consists of one platform company and one supplier. Along with an offline distribution channel, the supplier can choose two alternative online selling modes (i.e. the reselling and agency modes) to sell its product through the online marketplace. This paper applies Stackelberg game to derive the equilibrium with different business scenarios and selects the optimal online channel modes for two parties, respectively. Moreover, this paper extends to a different supply chain with a reverse channel leadership and a different product return policy for testing the robustness.

Several interesting and important results are derived in this paper. Firstly, it is found that the relative pricing are largely relied on the costs of two channels. Secondly, the platform supply chain may benefit from a pure channel rather than the dual-channel when this channel enjoys a relatively low cost and/or a sufficiently high consumer preference. Then, the platform and the supplier act contradictorily when selecting their optimal online channel modes. To be specific, the platform motivates to choose the online reselling mode when both the commission rate and the slotting fee are relatively low, whereas the supplier is likely to select the online agency mode under this circumstance. Finally, a win-win situation in regards to the optimal online channel mode for two parties is achievable with numerical experiments.

Based on the analytical studies, the results derived in the authors’ work can provide managerial insights to assist the supplier and the platform company in determining the operational decision and selecting the optimal online channel mode to deal with consumer returns. In addition, appropriate commission rate along with slotting fee will make both parties achieve a win-win situation in determining their optimal online channel mode.

To the authors’ best knowledge, this paper makes the first move to determine the optimal online channel mode in the content of consumer returns and study how it is affected by different product return policies.

This study, grounded in the SOR theory, aims to enrich the understanding of customer citizenship behaviour in omnichannel fashion retail by examining how different customer experiences enhance customer engagement and how that engagement leads to customer citizenship behaviour. The influence of return policies on the relationship between customer engagement and customer citizenship behaviour was also examined.

Partial least squares structural equation modelling (PLS-SEM) is used to examine the framework of the proposed study with data collected through a survey (n = 251) to examine the opinions of the respondents about the variables mentioned. The authors also assessed the proposed framework using predictive power assessment using PLS predict.

The study results reveal that customers’ experiences of integration and flexibility in omnichannel retail are positively associated with their engagement. However, customer experiences of connectivity, consistency and personalization do not appear to affect customer engagement significantly in omnichannel retail. The return policy positively moderates the relationship between customer engagement and customer citizenship behaviour in the omnichannel fashion retail context. Predictive power assessment shows that the proposed model has high prediction accuracy.

This study contributes to the marketing literature by investigating different dimensions of consumer experience collectively and its impact on customer engagement and citizenship behaviour. Furthermore, the study contributes to omnichannel retail in fashion industry by testing the return policy as a moderator variable on the relationship between customer engagement and citizenship behaviour.

Este estudio, basado en la teoría SOR, enriquece la comprensión del comportamiento cívico del cliente en el comercio minorista de moda omnicanal examinando cómo las diferentes experiencias del cliente mejoran el compromiso de éste y cómo dicho compromiso conduce al comportamiento cívico del cliente. También se examina la influencia de las políticas de devolución en la relación entre el compromiso del cliente y el comportamiento ciudadano del cliente.

Se utilizó la modelización PLS-SEM para examinar el marco del estudio propuesto con datos recogidos mediante una encuesta (n = 251) para examinar las opiniones de los encuestados sobre las variables mencionadas. Los autores también evaluaron el marco propuesto mediante una evaluación del poder predictivo utilizando la predicción PLS.

Los resultados revelan que las experiencias de integración y flexibilidad de los clientes en el comercio minorista omnicanal se asocian positivamente con su compromiso. Sin embargo, las experiencias de los clientes de conectividad, coherencia y personalización no parecen afectar significativamente al compromiso del cliente en el comercio minorista omnicanal. La política de devoluciones modera positivamente la relación entre el compromiso del cliente y el comportamiento ciudadano en el contexto del comercio minorista de moda omnicanal. La evaluación del poder predictivo mostró que el modelo propuesto tenía una alta precisión de predicción.

El estudio contribuye a la literatura de marketing investigando colectivamente diferentes dimensiones de la experiencia del consumidor y su impacto en el compromiso del cliente y el comportamiento ciudadano. Además, este estudio contribuye a la venta minorista omnicanal en la industria de la moda al probar la política de devoluciones como variable moderadora de la relación entre el compromiso del cliente y el comportamiento ciudadano.

本研究以 SOR 理论为基础, 通过研究不同的顾客体验如何提高顾客参与度, 以及顾客参与度如何推动顾客公民行为, 丰富了对全渠道时尚零售中顾客公民行为的理解。研究还探讨了退货政策对顾客参与和顾客公民行为之间关系的影响。

本文采用 PLS-SEM 模型来检验拟议的研究框架, 并通过调查（n = 251）收集数据, 以检验受访者对上述变量的看法。作者还通过使用 PLS 预测评估预测能力, 对提出的框架进行了评估。

通过调查（n = 251）收集的数据, 使用 PLS-SEM 模型来研究拟议的研究框架, 以考察受访者对上述变量的看法。作者还通过使用 PLS 预测评估预测能力, 对提出的框架进行了评估。

研究结果表明, 顾客在全渠道零售中对整合性和灵活性的体验与他们的参与度呈正相关。然而, 顾客在连通性、一致性和个性化方面的体验似乎并未对顾客参与全渠道零售产生显著影响。退货政策对全渠道时尚零售中顾客参与和公民行为之间的关系起到了积极的调节作用。 预测能力评估表明, 所提出的模型具有较高的预测准确性。

本研究通过对消费者体验的不同维度及其对顾客参与和公民行为的影响进行综合研究, 为营销文献做出了贡献。此外, 本研究通过检验退货政策作为顾客参与和公民行为之间关系的调节变量, 为时尚行业的全渠道零售做出了贡献。

The authors analysed the operations of two synchronised channels by focusing on “buy online and return in store” (BORS) strategies in fast-fashion retail by investigating internal and external factors affecting this omnichannel strategy.

The authors apply a combination of techniques to identify the BORS factors. Firstly, a strengths, weaknesses, opportunities and threats (SWOT) analysis was used to define the operational factors of BORS adoption. The authors then apply analytic hierarchy process (AHP) to evaluate the factors under four SWOT categories for kids, male and female consumer groups. The factors of BORS were then ranked using the fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (fuzzy VIKOR) approach.

Combining the SWOT, AHP and fuzzy VIKOR techniques, the authors identified 21 factors in this study. The opportunity that BORS provides for trying in the fitting room for a better convenient shopping experience was ranked as the most important factor, followed by the opportunity to create a loyal customer profile with an easy and well-organised return process. Furthermore, the results reveal that the child consumer group is the most critical of the stated operations factors, followed by male and female consumers.

The authors described the operational factors and supported the decision-making system of BORS for each consumer group with a priority ranking to realise effective managerial management for fast-fashion retailers and practitioners.

The study contributes to the growing literature on the BORS omnichannel strategy, specifically for fast-fashion retail based on consumer needs.

This study aims to examine the relationship between the risk-aversion level of return policies and customer trust in online shopping in three countries in the Middle East.

In the first step, the different types of return policies of online shoppers and the risk-aversion level were determined by surveying 18 online shops and interviewing 21 customers. The risk-aversion level of these policies was found in the experts’ panel. In the second step, the experiences of 573 consumers when facing seller’s return messages, perceived risk and consumer trust in three countries (UAE, Iraq and Iran) were collected through a questionnaire. Finally, the gathered data were analyzed using structural equation modeling.

The results indicated that risk-averse return policies taken by online vendors led to lower consumer trust. Moreover, customer perceived risk mediated the relationship between return policies’ risk-aversion level and trust in Iraq and Iran. At the same time, there was no significant association between return policies and perceived risk in UAE. In addition, perceived risk wholly mediated the relationship between return policies’ risk aversion and trust in vendors in Iran, but this role was minor in Iraq.

Among the intercultural studies, especially in the Middle East, this is one of the first studies based on the marketing and sales management in an online shopper’s supply chain. Moreover, the investigation of return policies in online commerce is another innovative aspect of the present paper.

As e-commerce has expanded rapidly, online shopping platforms have become widespread in India and throughout the world. Product return, which has a negative effect on the E-Commerce Industry's economic and ecological sustainability, is one of the E-Commerce Industry's greatest challenges in light of the substantial increase in online transactions. The authors have analyzed the purchasing patterns of the customers to better comprehend their product purchase and return patterns.

The authors utilized digital transformation techniques-based recency, frequency and monetary models to better understand and segment potential customers in order to address personalized strategies to increase sales, and the authors performed seller clustering using k-means and hierarchical clustering to determine why some sellers have the most sales and what products they offer that entice customers to purchase.

The authors discovered, through the application of digital transformation models to customer segmentation, that over 61.15% of consumers are likely to purchase, loyal customers and utilize firm service, whereas approximately 35% of customers have either stopped purchasing or have relatively low spending. To retain these consumer segments, special consideration and an enticing offer are required. As the authors dug deeper into the seller clustering, we discovered that the maximum number of clusters is six, while certain clusters indicate that prompt delivery of the goods plays a crucial role in customer feedback and high sales volume.

This is one of the rare study that develops a seller segmentation strategy by utilizing digital transformation-based methods in order to achieve seller group division.

This study aims to investigate the conditions for the financial feasibility of an incentive-based model for self-drop or crowdsourced drop of the product to be returned at designated drop boxes (thereby ensuring a contactless process).

Constraint-based non-linear mathematical modeling was done for cost differential with and without crowdsourcing. This was analyzed against returns on investment for the installed infrastructure. Scenarios were looked into from the linear, iso-elastic and logarithmic demand functions to identify the optimal incentive policy. The results were further evaluated using “willingness to return” for customer willingness for product returns via drop boxes.

Crowdsourcing is viable when product returns are no more than 15%–20% of the overall products, with a logistics cost differential of 15%–25%. These were only viable when the product return incentive was within the range of 15%–20% of the product cost, as well as the penalty was in the range of 25 to 40% for wrong returns.

The findings are expected to aid the organizations in successfully designing product return policies while adhering to the post-COVID-19 norms, including contactless transactions and social distancing.

The study provides a look into the viability sensitivity of effective gains/profitability against the required level of service for returns, wrong returns, penalties and incentives for crowdsourcing in a developing country like India.

With the growth in online purchasing, the return of distressed shipments also increased. The return experience of the online shopper has a huge impact on their next purchase decision-making. This explanatory research aims to identify and empirically explain factors related to the online buyer’s return experience that influence the repurchase intention of young buyers.

Primary data were collected from 235 active online young buyers who have experienced returning the goods through a structured questionnaire. Structural equation modeling is used for analyzing the data.

This study reveals that an online return policy leniency strongly supports service recovery quality, expected return convenience, buyer trust and satisfaction, which lead to repurchase intentions. Moreover, return satisfaction positively impacts repurchase intention while mediating young buyer trust.

This study is one of the few relevant pieces of research that would benefit e-tailers to improve their product return policy and compel young buyers’ intention to make a repeat purchase.

Climate change and digitisation are unquestionably the two defining features of this era. Both present immense challenges with unimaginable consequences for humankind while promising enormous rewards for those who can adequately address their adverse effects. These two critical factors must be considered while establishing strategies for the businesses' future operations. Hence, post-pandemic, especially with the rise of online commerce, packages and documents are delivered around the globe nearly every day, propelling the logistics industry's growth. This is not the critical challenge in logistics, the issue of sustainability, particularly as the returns are increasing exponentially, leading to a significant impact on transportation is and its reliance on fossil fuel has made it a prime target for society's growing environmental concerns. Thus, real-time visibility, collaboration and integration in reverse logistics (RL) are imperative for business sustainability. The most applicable Industry 4.0 technologies in RL are the Internet of Things (IoT), cloud computing, blockchain and digital twin that enable the defragmentation of the RL market.

This chapter analyses the technological impact of Industry 4.0 on RL. This research investigates the challenges faced by the logistics industry in the context of sustainability and how digital transformation can bring many potential benefits across the entire value chain. This chapter also presents a guidance for a framework based on the literature review that tends to favour the development of elastic logistics, implying improved company responsiveness to market conditions. The study contributes to the body of literature and the establishment of the framework for planning on the application of various Industry 4.0 technologies in developing eco-friendly and sustainable reverse logistics framework.

This study uses the antecedents, decisions and outcomes (ADO) framework to identify how perceived risks and benefits relate to the omnichannel strategy and influence consumer behavior.

A systematic review was conducted on 111 articles (2014–2023) on Scopus using NVivo® software for content analysis.

The literature on omnichannel is fragmented between journals and lines of research, making it difficult to identify influential journals in the area and preventing effective convergence. When the perception of risk is greater than the perception of benefits, companies must understand how to mitigate the risk, so that the adoption of an omnichannel strategy is not canceled.

The review is limited to one database and does not consider specific products/services or consumer profiles.

This review broadens understanding of omnichannel from a perspective neglected by researchers, namely risks and benefits and their impacts on organizational results. The model will clarify how the literature on omnichannel has evolved and instigate new research.