Search results

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 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 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.

This study aims to present a methodology and a system to support the technical and managerial issues involved in anomaly detection within the reverse logistics process of an e-commerce company.

A case study approach is used to document the company’s experience, with interviews of key stakeholders and integration of obtained evidence with secondary data.

The paper presents an algorithm and a system to support a more efficient and smart management of reverse logistics based on a set of anticipatory actions, and continuous and automatic monitoring of returned goods. Improvements are described in terms of a number of key performance indicators.

The analysis and the developed system need further applications and validations in other organizational contexts. However, the research presents a roadmap and a research agenda for the reverse logistics transformation in Industry 4.0, by also providing new insights to design a multidimensional performance dashboard for reverse logistics.

The paper describes a replicable experience and provides checklists for implementing similar initiatives in the domain of reverse logistics, in the aim to increase the company’s performance along four key complementary dimensions, i.e. time savings, accuracy, completeness of data analysis and interpretation and cost efficiency.

The main novelty of the study stays in carrying out a classification of anomalies by type and product category, with related causes, and in proposing operational recommendations, including process monitoring and control indicators that can be included to design a reverse logistics performance dashboard.

By examining the impact of product innovation on abnormal financial returns following the launch of new products, this study aims to test the explanatory power of a new compound measure of product innovativeness (Ganbaatar and Douglas, 2019).

It is a longitudinal study in which the authors used the compound product innovativeness score (CPIS) for the first time to measure product innovativeness. The abnormal financial returns are estimated through the event study design, where four different models are used. Artificial neural network analysis is done to determine the impact of the CPIS on abnormal returns by utilising a hexic polynomial regression model.

The authors find effect sizes that substantially exceed practically significant levels and that the CPIS explain 65% of the variance in the firm’s abnormal returns in market valuation. Moreover, new-to-the-market novelty predicts 83% of the variation, while new-to-the-firm (catch-up) innovation insignificantly impacts firm value.

This paper demonstrates how the CPIS, an objective and direct measure of product innovativeness, can be used to gain more insight into the innovation effect.

Implications for the business practice of this study include the necessity of relentless innovation by firms in contested differentiated markets, particularly where technological advance is ongoing. Larger and mature firms must practice corporate entrepreneurship to renew their products on a continuous basis to avoid slipping backwards in their markets. Innovation leadership, rather than following the leader, is also important to increase competitive advantage, given the result that innovation followship does not produce abnormal financial returns.

In this study, the authors focused on the effect of product innovativeness on firm performance. While the literature affirms a positive relationship between innovation and firm performance, the effect size of this relationship varies, due largely to the authors contend to simplistic measures of innovativeness. In this study, the authors adopt the relatively novel “compound” measure of product innovativeness (Ganbaatar and Douglas, 2019) to better encapsulate the nuances of both technical novelty and market novelty. This measure of product innovativeness is applicable to firms of all sizes but is more easily applied to entrepreneurial new ventures and SMEs, and it avoids the shortcomings of prior firm-level and subjective measures of innovativeness for both smaller and larger firms. Using a more effective analytical method (Artificial Neural Network), the authors investigated whether there is a “practically” significant effect size due to product innovation, which could be valuable for entrepreneurs in practice. The authors show that the CPIS measure can very effectively explain abnormalities in the stock market, exhibiting a moderate effect size and explaining 65% of the variation in abnormal returns.

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.

The purpose of this paper is to identify the influence of product information on purchase intention and evaluate the moderated mediation effect of return policy leniency in cross-border e-commerce.

The methodology is to use multiple regression analysis on 406 qualified online survey responses to determine the influence of product description, product display, and product content on consumer purchasing intention through product involvement as well as the moderated mediation effect of return policy leniency.

The results show that product description and product content were positively associated with product involvement, while product display did not exhibit a significant relationship between it and product involvement. As hypothesized, product involvement mediated the relationship of product description and product content with consumer purchasing intention. The return policy leniency was also found to positively moderate the mediation path of product content on purchasing intention through product involvement.

This study bridges a gap in the literature on the influence of three kinds of product information on purchasing intention through product involvement in a cross-border e-commerce context. Especially the study is one of the first attempts to determine that good return policy do not apply universally due to implied boundary conditions. The results can be used to expand consumption in cross-border e-commerce.

The advent of digitalization and the trend of social distancing coincide with the individualized lifestyle that is emerging among contemporary shoppers. This study explores the unique market of “smart solo shoppers”. Two empirical studies are conducted, which aim to identify the major dimensions of multi-channel shopping activities that are engaged by the shoppers (Study 1, n = 64) and to differentiate the shoppers' valuation of time invested in the distinct dimensions under different cultural influences (Study 2, n = 519).

A survey questionnaire is used for data collection, and data are analyzed using structural equation modeling.

Results reveal that the shopping activities converge into four principal dimensions: offline shopping, online shopping, post-shopping delivery and product return activities. Shoppers who perceive offline shopping activities as a time burden and online shopping and delivery activities as venues of value creation are more strongly self-identified as smart solo shoppers. Furthermore, smart solo shoppers who are under a strong influence of individualistic culture are found to spend time on multi-channel shopping to make the right purchase the first time, whereas shoppers perceiving being in a weak individualistic culture prefer to engage online channels while being prepared to return the unwanted purchases.

This study highlights an emerging research field in the nexus of solo consumption and smart shopping. Emphasizing the utility-driven and ego-expressive nature of smart solo shoppers, the authors provide an initial profile of these shoppers based on their time-valuation patterns and the contextual impacts of individualistic culture.

This study investigates the impacts of return channel type on the relationships between return service quality (RSQ) and customer loyalty (CL) in an omnichannel retailing environment.

Data comes from Chinese customers having a return experience in omnichannel retailing that uses the channel type of both buy-online-return-in-store (BORIS) and buy-in-store-return-to-online warehouses (BSROW). The authors use the structural equation modeling to test the hypotheses and the bootstrapping method to test the mediation and moderation effect.

For BORIS channel, satisfaction of customer returns (CRS) partially mediates the relationship between convenience and CL, and fully mediates that between CL and responsiveness, transparency and competence, respectively. For BSROW channel, CRS partially mediates the relationship between responsiveness and CL, and fully mediates that between CL and convenience, transparency and competence, respectively. The mediation effects indicate that omnichannel customers may feel more satisfied due to higher omnichannel fulfillment (responsiveness and convenience) and omnichannel trust (transparency and competence) provided by retailers. Return channel type moderates the relationship between RSQ-convenience and CL. The results show the different expectations between BORIS and BSROW customers in the return process.

This paper serves as a pioneering study to apply cognition-affect-behavior paradigm into the field of return management in omnichannel retailing.

The findings suggest retailers develop their strategies on customer returns and post-sales service quality improvement in the omnichannel. Also, retailers should develop an integrated return system across channels to provide convenient service to BORIS customers and quick response to BSROW customers.

Studying return service management in the omnichannel from customer's cognition appraisal, this study contributes to the literature of the reverse service management by bringing in the effect of omnichannel type to explore the relationship between RSQ and CL.