Omnichannel Retailing Research Articles

Role of bigdata analytics in improving drivers of omni-channel retailing for improving logistics experience

PurposeThe objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics.Design/methodology/approachUsing exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing.FindingsFindings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported.Practical implicationsThis study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC.Originality/valueThe study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.

Incorporating risk aversion and time preference into omnichannel retail operations considering assortment and inventory optimization

An omnichannel retail network includes an omnichannel retailer (o-retailer) determining which products among the candidate set are offered via an online or offline channel, and then procuring these products from the supplier and distributing them from a distribution center (DC) to physical stores for serving customers. The o-retailer adopts either the distribution center or physical stores to fulfill online orders. This study considers an integrated approach to manage assortment planning, inventory control and e-fulfillment problems and develops a distributionally robust optimization model, in which the distribution of uncertain demand is only partially available in advance. In the proposed model, the worst-case mean-Conditional Value-at-Risk (WMCVaR) is formulated as the objective function that makes a trade-off between the expected profit and the risk, and a quasi-hyperbolic discounting function is adopted to denote the customers’ time preference. Furthermore, to overcome model solvability obstacle caused by imprecise probability distributions, the box ambiguity set is applied to derive computationally tractable counterparts. Numerical studies are conducted to investigate the validity and efficiency of our proposed model. Some useful managerial insights and implications for o-retailers are generated through the analyses of computational results.

Robust pricing and inventory strategies for an omnichannel retailer under carbon tax and cap-and-offset regulations

While an increasing number of retailers use the buy-online-and-pick-up-in-store (BOPS) service to improve operational efficiency, it increases the uncertainty between the offline and online channels. Furthermore, the implementation of different carbon regulations creates certain challenges for an omnichannel retailing system because of the tradeoff between the economy and the environment. These factors motivate us to study the joint pricing and inventory decisions of an omnichannel retailer regrading the stochastic demand of BOPS customers with limited information under carbon tax and cap-and-offset regulations. A distributionally robust newsvendor model is developed for the omnichannel retailer under carbon tax regulation to derive the joint decisions on the sales price and inventory. An interesting result indicates that under carbon tax regulation, differential pricing strategy increases the profit of the omnichannel retailer. The distributionally robust newsvendor model under cap-and-offset regulation is solved by the Karush-Kuhn–Tucker (KKT) conditions. The comparison shows that adopting uniform pricing strategy under cap-and-offset regulation brings more profits than adopting it under carbon tax regulation. Finally, a numerical study is conducted to illustrate and complement the theoretical results. The value of addition demand information is also tested. Key findings show that the omnichannel retailer gains higher profit and emits more carbon emissions under cap-and-offset regulation than under carbon tax regulation. Under each type of regulation, the performance of robust solutions is close to that with normal distribution.

The mediating role of perceived enjoyment and attitude consistency in omni-channel retailing

PurposeThis study considers perceived enjoyment and attitude consistency as internal states of consumers in an omni-channel environment. This study aims to investigate the mediating role of perceived enjoyment and attitude consistency to reveal how omni-channel environment factors of interaction fluency, convenience, price advantage and personalization contribute to omni-channel shopping intention.Design/methodology/approachConsumers who had shopped at Uniqlo's online and offline stores were surveyed through an online questionnaire, and 566 data were collected for analysis through partial least squares structural equation modeling (PLS-SEM).FindingsThe results find that interaction fluency, price advantage and personalization positively affect perceived enjoyment, interaction fluency and convenience positively affect attitude consistency and perceived enjoyment and attitude consistency in turn facilitate omni-channel shopping intention. The mediating role of perceived enjoyment and attitude consistency was confirmed.Originality/valueThe original finding of this study is that factors such as interaction fluency, convenience, price advantage and personalization in omni-channel retailing require momentary and continuous affective states of consumers to facilitate omni-channel shopping intention, respectively. Therefore, this study considers the necessity of capturing different affective states of consumers in omni-channel shopping.

Consumer Behavior in Omnichannel Retail

Consumer Behavior in Omnichannel Retail

Customer experiences in omnichannel retail environments: a thematic literature review

ABSTRACT The paradigm shift towards omnichannel approaches represents an ongoing fundamental change and a key metamorphic process taking place within the fields of retail marketing and management today. The intertwining of commerce and content across channels and touchpoints requires retailers to reconfigure their strategies and manifests new challenges for grasping concepts like customer experience and customer journeys. In response to these developments, we conduct a thematic review of 64 academic papers addressing customer experiences in omnichannel retail environments, integrating central concepts and approaches and thereby contributing to the body of literature exploring new and alternative approaches and theories to customer experiences along omnichannel customer journeys. We identify 8 overlapping streams of literature in this regard, highlightig that research on the subject tends to be focused on the seamlessness of channel integration and efficiency and thus might benefit from more consumer-centric, interdisciplinary work taking the co-creational aspect of these experiences into account. We contribute to retail – and omnichannel literature as well as retail branding theory and practice.

Managing omni-channel reverse logistics risk during supply chain disruption recovery in the South African fashion industry

Background: Omni-channel retailing is blurring the lines between online and physical stores for consumers as it provides consumers with more choices, convenience and a seamless shopping experience. An integral aspect of implementing an omni-channel retail strategy is having an efficient reverse logistics process. However, retailers seem reluctant to implement omni-channel reverse logistics because of the various risk types that affect the economic wellbeing of a firm, especially during supply chain disruption recovery (SCDR) when the firm is in distress. Prior research primarily examines the risks associated with reverse logistics in a single channel. While the existing findings are promising, there is a lack of understanding regarding the specific risks involved in omni-channel reverse logistics and how to mitigate these risks in the context of SCDR.Objectives: The purpose of this study was to explore omni-channel reverse logistics risks and mitigation strategies during SCDR in the South African fashion retail industry.Method: The study employed a generic qualitative design using purposive sampling methods. Fourteen semi-structured interviews were conducted to collect data. The data were analysed using a thematic analysis approach.Results: The study identified specific types of omni-channel reverse logistics risks. The findings indicate that omni-channel reverse logistics risk during SCDR is managed through proactive and reactive strategies such as technology implementation, collaborative relationships, quality insurance inspections, customised policy changes and disruption-specific reverse logistics teams. The findings show that mitigating omni-channel reverse logistics risk can help create a competitive advantage because of increasing customer loyalty, value recovery and profits.Conclusion: The findings provide valuable insight on how to manage omni-channel reverse logistics risk during SCDR and, if mitigated correctly, can contribute to a competitive advantage.Contribution: This study expands on the current literature by identifying multiple types of omni-channel reverse logistics risks and strategies used to manage omni-channel reverse logistics risk in a SCDR context.

Spirit & Free: adapting assortment strategies across rapidly growing channels in fashion retail

Social implications This paper aims to describe the cross-channel challenges experienced by a leading US fashion retailer and illustrates the adaptation to consumer needs as led by a female divisional head and female executive. Learning outcomes The teaching objectives include to understand the assortment planning complexities experienced by merchandise managers; address critical issues surrounding channel strategies; identify the data needs for assortment improvement and cross-channel management; investigate responsive solutions for customer-focused assortment diversification; and explore the challenges associated with continual retail channel adaptation. Case overview/synopsis The fashion retailer Spirit & Free (S&F) (pseudonym) is a Fortune 500 retailer. As a multi-channel retailer, S&F is proud of the consistency of the brand’s identity across channels. However, recently, S&F has noticed a difference between their mobile (m-commerce, social commerce) and in-store/e-commerce customers. Through this case study, students will follow the Women’s Apparel Divisional Merchandise Manager and explore how the business will maintain a consistent brand identity and capture both sets of customers through assortment planning. Resources will be provided for assortment planning analysis, and students will be asked to consider assortment opportunities regarding category mix and pricing strategy. Complexity academic level The case would be relevant to upper-level undergraduate courses or introductory master's level course in retail, management, fashion merchandising and omni-channel retail. Supplementary materials Teaching notes are available for educators only. Subject code CCS 8: Marketing

Optimal Joint Assortment for an Omni-Channel Retailer

With the growing popularity of e-commerce, nearly every prominent retailer is aiming to turn omni-channel. One crucial decision in this pursuit is the identification of the joint assortment. In this study, we contribute by examining joint assortment and product prices for a retailer that sells products through both brick-and-mortar and online channels. Our analysis indicates that the optimal assortment should be thought of as a portfolio of two types of products: customized and omni-channel. Customized products are priced in such a way that they are targeted toward customers who prefer to shop from the channel the products are sold through. In contrast, omni-channel products are priced attractively so that all customers consider buying them. The relative mix of these products depends on how flexible customers are in shopping from the channel they do not prefer and the number of customers who prefer each channel. Additionally, we investigate whether the conventional wisdom of selling niche products through the online channel is always optimal. We find that this suggestion may be sub-optimal when the online channel has greater cost of including a product in the assortment and fewer preferring customers compared with the brick-and-mortar channel.

The effect of personal innovativeness on customer journey experience and reuse intention in omni-channel context

PurposeThis study aims to investigate customers' personal innovativeness (PI) as an influencing factor of omni-channel customer experience throughout pre-purchase, purchase and post–purchase stages of the customer journey, and their subsequent influences on customers' reuse intention.Design/methodology/approachData were collected from customers who had experience with omni-channel shopping in South Korea through a questionnaire made with Naver Forms, both online and offline from 15 June to 15 July 2022. Out of the received responses, only valid and consistent questionnaires were considered for statistical analysis. In total, 272 valid samples were utilised for the final analysis. Analyses included reliability, validity, path, structural equation modelling and mediation effects, using SPSS and AMOS software.FindingsThe results revealed a significant influence of personal innovativeness on the omni-channel customer experience across all purchase stages. Personal innovativeness was found to influence the customer experience in the pre- and post–purchase stages, thus affecting reuse intention. However, it did not have the same effect in the purchase stage. The omni-channel experience customer experience also played an indirect mediating role in the relationship between personal innovativeness and reuse intention.Research limitations/implicationsFirst, personal innovativeness in the IT domain may be very prominent in studies examining innovative behaviours related to computing technology. Second, this study provides further understanding of customers' intentions to reuse omni-channel shopping. Third, the path analysis showed that personal innovativeness significantly affects customer experience at all pre-purchase, purchase and post–purchase stages of the customer journey. However, except for the purchase experience, both pre- and post–purchase experiences significantly impact customers' intention to reuse omni-channels and play a mediating role.Practical implicationsFirst, omni-channel retailers should launch new products, innovative promotional activities and explore new channels or new service modes to stimulate the need recognition of customers with high personal innovativeness. Second, omni-channel retailers should pay attention to the users' reviews of each channel because they play a key role in potential customers' purchase decisions. Third, offering customers a seamless shopping experience is essential as a marketing strategy for omni-channel retailing.Originality/valueThis study elucidates the causal relationship between personal characteristics and behaviour by dividing the omni-channel customer journey. In particular, personal innovativeness is identified as an important predictor of the intention to reuse omni-channels during the pre- and post–purchase stages. This suggests that omni-channel retailers need to strategically manage these stages to boost customers' reuse intention.

Integrated optimization of assortment, inventory and pricing considering omnichannel retailer’s risk aversion and customer’s time preference

This paper mainly discusses the joint optimization of product assortment, inventory and pricing for an omnichannel retailer under uncertain demand, seeking to maximize the retailer’s Worst-case Conditional Value-at-Risk (WCVaR) based profit and customer’s expected utility. The risk aversion of decision-maker and the time preference of customers are depicted by the WCVaR and quasi-hyperbolic discounting function, respectively. A bi-objective stochastic optimization model is developed. To alleviate the computational burden, a linearization method is applied to convert the problem into a mixed integer linear programming that proves to be solvable within reasonable CPU times using the augmented ε-constraint method. Numerical studies are conducted to investigate the applicability of the proposed model and the efficiency of the solution approach. Our experimental results show that offering customers with high expected utility typically requires low prices and small assortments. We also make other counterintuitive observation that the price of products sometimes increases when the expected utility increases. Furthermore, WCVaR has superiority compared with the risk-neutral model in terms of robustness and stability. The time preference of customers has non-negligible impacts on decision-making results. In addition, the further sensitivity analyses investigate the impacts of various key parameters on the performance of omnichannel retailing.

Centralized Decision Making in an Omnichannel Supply Chain with Stochastic Demand

With retailers increasingly adopting the omnichannel retailing model as a core strategy in their daily operations, this study investigates the impact of random demand on the omnichannel supply chain that employs a combination of the online channel, retail channel, and buy online and pick up in store (BOPS) channel, in light of the more stochastic market after the occurrence of COVID-19. To enhance the sustainable profitability of the omnichannel supply chain, this study considers price and lead time dependent demand with both known and unknown distributions, and establishes mathematical models to maximize profit under centralized situations. The study analyzes the variations in demand with lead time in the three channels and examines the effects of price and lead time on profit. Additionally, it investigates the interactions between price and lead time. Through numerical examples, the study illustrates the effects of the mean and variance of random demand on decision variables and examines the influence of potential demand and the sensitivity of lead time. Overall, this analysis provides valuable insights into the impact of demand randomness on the profitability of an omnichannel supply chain, highlighting the importance of considering price and lead time in the decision-making process.

Analysing the Impact of Omni-channel Customer Delight on Repurchase Intention

Merely satisfying the customers is not enough; delighting them by offering unexpected, innovative and surprising services has become crucial. For this, firms invest in several channels and attract delighted customers. The current research examines the impact of Omni-channel customer delight on customers’ repurchase intention. The proposed conceptual model develops several hypotheses relating to customer delight in the Omni-channel context by reviewing rich literature on customer delight. Data were collected from 496 respondents using convenience sampling, representing 24 states of India. Using Smart PLS software, collected data were examined through structural equation modelling. Surprise and joy are crucial to offline customer delight, while satisfaction, usefulness and entertainment play significant roles in online customer delight. Also, Omni-channel customer delight significantly influences repurchase intentions; therefore, paying attention to all antecedents of customer delight is essential. The research provides a basic understanding of customer delight in Omni-channel contexts and offers directions to formulate various strategies to delight customers beyond satisfaction. The article adds value to existing knowledge relating to Omni-channel retailing. Omni-channel customer delight is undoubtedly an emerging research domain in the current Omni-channel retailing.

Does pickup service quality explain BOPIS users' store relationship performance? The moderating role of users' service experience consciousness

PurposeBuilding on Stimulus-Organism-Response theory, the current study examines the influence of pickup service quality in buy-online pickup in-store service (BOPIS) on users' perceived relationship investment with the mediating role of users' perceived experience quality and relationship proneness. This research also demonstrates the subsequent impact of BOPIS users' perceived relationship investment on their relationship performance indicators, like their cross-buying behaviors (breadth), frequency of their purchase (depth) and longevity of their relationship (length) with the store. The moderating role of BOPIS users' service experience consciousness in a few proposed relationships was tested.Design/methodology/approachThe research is descriptive, quantitative and cross-sectional investigation. The study employed a purposive sampling technique. It was conducted using data collected using a validated self-administered questionnaire from 786 Indian omnichannel shoppers who have used BOPIS services in the past. The proposed conceptual model was tested using Partial Least Squares-Structural Equation Modeling.FindingsThe results indicate that BOPIS users' perceived experience quality and relationship proneness positively mediate pickup service quality and perceived relationship investment. The users' perceived relationship investment subsequently significantly positively impacts different dimensions of their relationship performance with the store (breadth, depth and length). Additionally, BOPIS users' service experience consciousness has a significant negative moderating effect on the direct relationship between pickup service quality and different dimensions of relationship performance.Research limitations/implicationsThe study is conducted in the Indian population, where omnichannel retailing is still nascent.Originality/valueThis study addresses the need to investigate the relationship performance indicators of BOPIS users, like their cross-buying behaviors(breadth), frequency of their purchase(depth) and longevity of their relationship(length) with the store. This study is the first to show that pickup service quality might explain the relationship performance of BOPIS users through their perceived experience quality, relationship proneness and relationship investments. The moderating role of BOPIS users' service experience consciousness in a few proposed relationships was also tested for the first time.

The impacts of omnichannel retailing properties on customer experience and brand loyalty: A study in the banking sector

The impacts of omnichannel retailing properties on customer experience and brand loyalty: A study in the banking sector

Challenges and Changes to the Product Development Process for Fashion Omnichannel Retailers

This paper focuses on the relatively limited research activity for Fashion Product Development (FPD). This work aims to challenge the traditional FPD theoretical process model within existing academic literature and presents a revised version which is underpinned by the concept of “robust management” derived from the New Product Development (NPD) literature and industry discussion. This new theoretical process model is a more accurate reflection of current practice within the fashion industry. The development of this research is influenced by critically investigating the product development process used by high street omnichannel retailers that develop “own label” fashion clothing, and which distribute products through high street stores and online sales channels as well as having integrated or overlapping service domains. The research examines the process inputs and outputs as well as the planning and management of the process overall and in so doing intends to capture the holistic nature of current industry FPD for omnichannel retailers. The empirical research proceeded using a qualitative approach using semi structured indepth interviews conducted with key informants from market leading retailers. The major findings of the research indicate that a new theoretical contribution to the academic literature field of FPD may be appropriate. The work illustrates the current product development process, documenting the challenges, changes and solutions that have influenced it, specific to omnichannel retailers, whilst identifying the links and parallels from NPD process model structures. This research explores the necessity of product development theoretical models that are specific to business and retail types within the fashion industry and contributes to the nascent theory that has a specific focus on fashion product development.

Green purchase intention in omnichannel retailing: role of environmental knowledge and price sensitivity

ABSTRACT This study explores how cross-channel integration influences consumers’ green purchase intention, specifically through psychological ownership, consumer skepticism, environmental knowledge, and price sensitivity. We collected data from Indian consumers, using an online questionnaire survey method. The data was collected from consumers using an online survey. The data were analyzed using mediation and moderated mediation models. Findings suggest that an increase in cross-channel integration does enhance consumers’ green purchase intention and that there is a significant mediating role of both consumer skepticism and psychological ownership. The results show that while environmental knowledge positively moderates the mediating path via psychological ownership at all levels (i.e. from low to high), it does not moderate the mediating path via consumer skepticism. Moreover, price sensitivity negatively moderates the mediating path via psychological ownership at all levels from low to high, while price sensitivity positively moderates the mediating path via consumer skepticism at all levels from low to high.

Mobility and the mall: Three solution pathways for efficient and sustainable omnichannel goods transportation for a mall in paris

Urban shopping malls do not only depend on consumer mobility to operate and thrive, but goods mobility as well. With the emergence of omnichannel retail, stores are now multifunctional hubs accommodating collection, delivery, and return of online purchases. As a consequence, goods transportation requirements for stores have intensified. This impacts the malls in which they are localized as well. The scientific literature that covers goods mobility and malls is fairly limited. It has not yet explored the efficiency and sustainability of goods transportation to and from malls in the omnichannel era. To perform a state of practice and suggest improvements, we combine case study and exploratory research for the Beaugrenelle mall in Paris. The research demonstrates three operational issues. First, chaotic supply operations resulting in alternative practices that expose delivery workers to financial, security, and ergonomic risks. Second, patchy delivery practices that are not aligned with the regular supplies. Third, a lack of storage. In response, we explore three solution pathways: i.e., introducing dedicated staff, engaging third parties, and implementing intelligent technology. In doing so, we intend to provide elements for discussion for the mall operator, the retail tenants, their logistics service providers and the city moving forward.

Research on predicting the impact of promotional activities on consumer behavior in omnichannel retailing

In recent years, the omnichannel sales model has rapidly emerged and is widely used in a context in which consumer buying behavior is influenced by a variety of factors that produce complex changes. Among these factors, the impact of omnichannel promotions on consumer behavior is particularly critical, and thus this research area has received much attention. Predicting the shopping feedback of different types of consumers with different numbers of promotions can help companies develop targeted promotional strategies and improve the consumer shopping experience. In this paper, we classify consumers into different types by clustering them in three dimensions: basic personal information, shopping preference, and shopping channel preference. Based on this, a machine learning prediction model based on the random forest algorithm is built in each of the three dimensions, and the model's performance is evaluated by plotting ROC curves. In order to improve the model's performance, this paper uses the up-and-down sampling method to balance the data. The prediction model based on consumers' "basic personal information", "shopping preference," and "shopping channel preference" has been successfully developed, and the prediction results are excellent. This study provides guidance for companies to develop targeted promotion strategies and offers new ideas and methods for marketing and data analysis. In the future, we can continue to dig deeper into consumer behavior data, classify consumers in more dimensions, build more accurate prediction models, and continue to improve the scientific and accurate promotion decisions of enterprises.

Predicting intention to adopt omnichannel retailing of SMEs in Indonesia using UTAUT: the moderating role of personal innovativeness

This study seeks to explain the intent of SMEs business owners to implement omnichannel retail in their operations. This study employs the UTAUT model and adds innovativeness as a variable that can influence the intention to adopt an omnichannel. The sample for this research consisted of 90 SMEs proprietors in Malang City. This study's data were gathered via a questionnaire and analyzed using PLS-SEM. This study found that personal innovativeness and performance expectations significantly influence the intention to adopt omnichannel. In this study, effort expectations have no significant effect on the intention to implement omnichannel. It has been demonstrated that personal innovativeness can moderate the relationship between effort and performance expectations in the UTAUT model when it comes to the intention of MSME proprietors to implement omnichannel. In addition to focusing on consumers as end users, this study concludes that omnichannel service providers must also consider enterprises as omnichannel users.