Multi-channel Environment Research Articles

Manufacturer’s decision-making and coordination strategy in an asymmetric multi-channel environment

This paper explores the significant impact of e-commerce and investigates manufacturers’ decision-making processes regarding the opening of e-shops and the adoption of online and offline coordination strategies to enhance profits in an e-commerce environment. A novel three-channel model with asymmetric retailers is proposed, and three scenarios are analyzed: the initial dual-channel scenario, the multi-channel scenario with e-platform, and the “Order online, Pickup offline” coordinated scenario. By comparing optimal profits across these scenarios, decision-making inequalities for manufacturers are derived. Subsequently, numerical experiments validate that manufacturers, aiming to maximize profits, opt to establish an e-commerce channel and coordinate with offline retailers. Additionally, the study emphasizes the importance of e-platforms in setting commission rates to drive increased profits. The findings offer practical implications for manufacturers to engage in interest-balanced coordination, enabling them to adapt to evolving retail dynamics in the advancing e-commerce landscape from both theoretical and practical perspectives.

Psychographic segmentation of multichannel customers: investigating the influence of individual differences on channel choice and switching behavior

This study investigates the role of individual differences in channel choice and switching behavior in a multichannel environment using latent class analysis on data from 1512 customers. Psychographic variables from five domains (risk attitudes, cognitive ability, motivation, personality, and decision-making style) serve as covariates for multichannel customer behavior. We identify six segments that differ significantly on six psychographic variables (readiness to take risks, need for cognition, autotelic and instrumental need for touch, and rational and intuitive decision-making styles). The results advance the theory-building of multichannel customer behavior and present insights for proactively managing customer journeys of distinct segments.

Market expansion through online-buying to store-pickup (O2S): Implications for end-to-end supply chain strategy

A growing body of literature examines the demand effects of the increasingly popular retailing strategies of integrating digital sales channels with brick-and-mortar stores, allowing customers to buy goods online for store pick-up. Implications of such initiatives have been explored for retailing but often ignored for the associated (upstream) sourcing strategy, which affects a critical success factor: product availability. To capture the full implications of online-to-store (O2S) initiatives, we present an analytical model of the end-to-end supply chain of a brick-and-mortar retailer expanding its market via O2S. We derive equilibrium product availability involving sourcing strategy and consumer choice in pre-and post-O2S cases to provide four insights into the interdependence of O2S and sourcing strategies. First, market expansion via O2S is moderated by the retailer's sourcing strategy and is achievable with only a subset of suppliers under certain conditions. Second, O2S introduction can render an existing supplier economically infeasible. This impact is exacerbated when the cost of processing goods returned by the retailer's O2S customers is high. Third, a market-expanding O2S strategy is profitable only in limited circumstances and can lower the retailer's profit even if the probability of product returns is small and returns processing is costless. Fourth, in some cases, it is beneficial for the retailer to change its supplier (e.g., from cost-efficient to demand-responsive) after introducing O2S. These results highlight the need to jointly plan the retail and sourcing strategies in a multi-channel environment to optimize the end-to-end supply chain.

Predicting the Use of Chatbots for Consumer Channel Selection in Multichannel Environments: An Exploratory Study

Online consumers are increasingly looking for more convenient ways to purchase products and services, and chatbots are becoming increasingly popular in multichannel environments due to their ability to provide an efficient service. In this context, managing digital complexity with the help of artificial intelligence and supporting decisions in a multichannel context is an appealing perspective for the retailer, who must find the right strategy to win and keep customers online. The present empirical study aims to better understand consumer behaviour in the multichannel environment in the context of four categories of products and services (retail banking, mobile communications, fashion, and consumer electronics) from the perspective of identifying determinants of channel selection when the consumer uses chatbots. Data were collected from 936 respondents with multichannel retail experience to conduct an empirical investigation on social media platforms, including Twitter, Facebook, and Instagram; these data were then analysed using structural equation modelling (SEM). We found that the online consumer’s multichannel behaviour was not only a reality in the field of broad purchasing decisions but already a norm, and consumers had good reasons to use more channels in the context of chatbots. Research results suggest that chatbots can represent a decision-making aid for managers in retail companies who want to develop an efficient and optimal logistics service strategy in multichannel environments.

An Energy-Efficient Multi-Channel Design for Distributed Wireless Sensor Networks

This article discusses the importance of designing an efficient medium access control (MAC) protocol for wireless sensor networks (WSNs) to optimize energy consumption at the data link layer while transmitting high traffic applications. The proposed protocol, EE-MMAC, is an energy-efficient multichannel MAC that reduces energy consumption by minimizing idle listening, collisions, overhearing, and control packet overhead. EE-MMAC utilizes a directional antenna and periodically sleep technique in a multi-channel environment. Nodes exchange control packets on the control channel to choose a data channel and decide the beam direction of the flow. Simulation results show that EE-MMAC achieves significant energy gains (30% to 45% less than comparable IEEE 802.11 and MMAC) based on energy efficiency, packet delivery ratio, and throughput.

A decision-making characteristics framework for marketing attribution in practice: Improving empirical procedures

In today’s multi-channel environment, It is becoming increasingly difficult to implement advanced multi-touch attribution (MTA) models to facilitate advertising decision-making. This is due to the rising number of advertising platforms, such as TikTok, Metaverse and Google — each with its own unique attribution principles — and the decline in user-level disaggregated data. Over time, the development of marketing models has matured in parallel with the greater availability of consumer data and understanding of consumer behaviour. To overcome media optimisation challenges at the tactical and channel levels, e-commerce brands have replaced traditional media-mix methods with attribution methods that provide immediate insights into return on advertising spend. However, existing MTA models lack simplicity, robustness, ease of interpretation, and accuracy, all of which are critical attributes of decision-supporting models. To address this, this paper proposes a holistic conceptual framework that captures the various interplaying characteristics of attribution models in practice. The concept is based on the evolution of modelling and insights into the development of decision-making paradigms. The proposed architecture highlights the interactions between various tools, media categorisation and metrics, and how they influence media spend optimisation at the channel and tactical levels. The paper also describes some of the most recent advances in media measurement practices. By adopting the proposed framework, future advertisers can identify the best way to overcome the challenges of analysing marketing performance.

The Intention to Cart Abandonment in the Context of Multi-Channel Pricing

Theoretical background: Shopping cart abandonment is defined as a situation when the customer chooses products but does not complete the financial transaction. The vast majority of research articles on purchase abandonment concerns the online or mobile environment. The presented research model refers to the customer intention to resign from purchasing both in physical store and via mobile app caused by a multi-channel pricing strategy. By analogy to many definitions of online cart abandonment, the author defines cart abandonment in a multichannel environment as a decision about postponing purchase at all, both in a physical store and in a purchase mobile app. One of the possibilities of consumer behaviour as a reaction to the multi-channel pricing may be purchase abandonment. The impact of price differentiation across channels on purchase abandonment still deserves research attention due to the lack of the unequivocal confirmation. Purpose of the article: Setting prices in a multichannel environment creates a vital challenge for multichannel retailers. This article attempts to explain one of the undesirable consequences of the channel based price differentiation, which is the purchase abandonment. The purpose of this paper is to identify factors influencing the customer intention to abandon the purchase under channel-based price differentiation conditions (physical store and mobile purchase app). Research methods: This study is a quantitative one employing a scenario-based approach to obtain responses from 500 participants. This research used the structural equation modelling to test its hypotheses. Main findings: Findings reveal positive impact of perceived limited self-determination and perceived price unfairness on intention to cart abandonment, whereas consumer trust in a mobile app can reduce the intention to resign from purchase. Furthermore, the author finds the indirect impact of the mobile app familiarity as well as the retailer brand awareness. Research results can help managers to reduce the likelihood of losing customers in the multi-channel pricing environment.

Enhancing Customer Experience with Personalized Data Strategies in Salesforce Data Cloud

Today’s companies rely on data to deal with customers and hence, personalization has become a major strategy for winning over customers. This paper aims to investigate improvement of customer experience with personalized data strategies in Salesforce data cloud. It focuses on analyzing the architecture of Salesforce Data Cloud, real-time analytics, activation features as well as its unification of data. The framework provides a clear view on how the organization should collect data, create a single customer view and progress to intelligent segmentation. The paper also aims at the management of customer interactions across the multichannel environment, using predictive insight and the sentiment of analysis to guide a real-time engagement. The dark side of hyper personalization including ethical implications and data privacy concerns is discussed in detail, as a call for responsible use of methods in data collection. Salesforce Data Cloud helps organizations to build and maintain meaningful customer relationships that create value and bring about increased and sustained organizational an organizational growth.

The Effects of Consumer Information Confusion and Choice Confusion on Purchasing-Related Behavior of Adult Men in Their 20s and 30s When Purchasing Basic Cosmetics in a Multi-Channel Environment

The purpose of this study is to understand the effects of consumer information confusion and choice confusion perceived by adult men in their 20s-30s on purchase-related behaviors for the purchase of basic skincare cosmetics in multichannel environment. The research subjects were adult men in their 20s-30s who had experiences in on/offline information search for the purchase of basic skincare cosmetics in Seoul, Gyeonggi, and Incheon region. From June 15 to July 15, 2022, an online survey using NAVER Form was conducted. Total 300 questionnaires were distributed and then 295 questionnaires were utilized for the final analysis after excluding five questionnaires with insincere responses. Using the SPSS WIN 21.0 Program for data analysis, this study conducted the frequency analysis, descriptive statistics analysis, factor analysis, correlation analysis, and multiple regression analysis. In the results of this study, when the information confusion got higher due to the overloaded information about basic skincare cosmetics on/offline, the behavior of delaying the purchase of basic skincare products was highly shown in adult men in their 20s-30s. Also, in case of the purchase of basic skincare cosmetics, there are many similar basic skincare cosmetic products in on/offline shops. When the confusion about the choice of basic skincare cosmetics suitable for one’s own skin type was higher, the behavior of delaying the purchase decision-making of basic skincare cosmetics was highly shown in adult men in their 20s-30s. In the results of this study, the adult men in their 20s-30s are facing much confusion about cosmetic information search and choice due to numerous cosmetic information on/offline, and also delaying their purchase for a moment as it is not directly connected to the purchase of cosmetics. This shows that the adult men in their 20s-30s are facing much confusion in the circumstance of choosing their basic skincare cosmetics among massive, exaggerated, and similar information about cosmetics in the information environment.

Lot-sizing and pricing decisions under attraction demand models and multi-channel environment: New efficient formulations

The presented paper considers the pricing and lot-sizing decisions for a manufacturer who produces and sells a single product in different selling channels i.e physical stock, website, mobile, etc. The objective is to find the production plan and prices of each channel to maximize the total profit defined from difference between the revenues and the productions, holding and setups costs. The consumers’ demand in each channel is represented by attraction demand models which include the multinomial logit (MNL), multiplicative competitive interaction (MCI) and linear demand models. The addressed problem is formulated as a non-convex mixed-integer nonlinear program (MINLP). Based on properties of attraction functions, an efficient reformulation which transforms the initial non-convex problem into a convex one is presented. Therefore, an optimization approach based on the outer approximation algorithm is presented to solve the problem. Numerical tests based on large benchmark of real inspired instances show the efficiency of the proposed approach to solve the addressed problem compared to the initial non-convex model.

Attentional Multi-Channel Convolution With Bidirectional LSTM Cell Toward Hate Speech Prediction

Online social networks(OSNs) facilitate their users in real-time communication but also open the door for several challenging problems like hate speech and fake news. This study discusses hate speech on OSNs and presents an automatic method to identify hate messages. We introduce an attentional multi-channel convolutional-BiLSTM network for the classification of hateful content. Our model uses existing word representation techniques in a multi-channel environment having several filters with different kernel sizes to capture semantics relations at various windows. The encoded representation from multiple channels passes through an attention-aware stacked 2-layer BiLSTM network. The output from stacked 2-layer BiLSTM is weighted by an attention layer and further concatenated and passes via a dense layer. Finally, an output layer employing a sigmoid function classifies the text. We investigate the efficacy of the presented model on three Twitter-related benchmark datasets considering four evaluation metrics. In comparative evaluation, our model beats the five state-of-the-art and the same number of baseline models. The ablation study shows that the exclusion of channels and attention mechanism has the highest impact on the performance of the presented model.The empirical analysis analyzing the impact of different word representation techniques, optimization algorithms, activation functions, and batch size on the presented model ascertains the use of their optimal values.

An 18.6-μW/Ch TDM-Based 8-Channel Noncontact ECG Recording IC with Common-Mode Interference Suppression.

This paper presents an 8-channel electrocardiogram (ECG) monitoring integrated circuit (IC) controlled by time-division multiplexing (TDM). The proposed TDM compensates the electrode DC offsets by forming an individual discrete-time feedback loop per channel while sharing an analog frontend. This enables a chopping-free open-loop amplification, achieving a high input impedance suitable for a noncontact ECG monitoring. In addition, a common-mode interference (CMI) cancellation scheme is also introduced in the proposed TDM schedule for the realization of a pseudo-driven-right leg (DRL) in a multichannel environment. The designed system is implemented in 180 nm CMOS. The chip dissipates 18.6 μW/channel including the power consumption by ADC. It shows the total-CMRR of 100 dB against CMI voltage swing up to 20 VPP. The chip is verified in noncontact 8-channel ECG using conventional passive electrodes.

Service Quality and Customer Satisfaction of Hotels in Port Harcourt, Rivers State

The study examined the relationship between service quality and customer satisfaction of hotels in Rivers State. The study adopted descriptive survey research design. The population of the study comprised all customers of registered hotels in Rivers State. This implies that the study population is infinite in nature. A sample size of three hundred and eighty-four (384) was adopted. The various hypotheses formulated were tested using Pearson Product Moment Correlation (PPMC). The results of the analysis confirmed that all the dimensions of service quality (assurance and service responsiveness) were found to have a positive and significant relationship with customer satisfaction as measured by customers’ loyalty and referrals. It is therefore concluded that the aim of service quality is to optimize customer satisfaction through gaining the loyalty of the current customers in a multi-channel environment and ensuring they are completely satisfied. In line with the conclusion, the study recommends that the hotel staff and employees should be well cultured and trained to provide prompt services to their guest when called upon to do so, as service responsiveness is seen as a major tool for guaranteeing customer referral behaviour.

Understanding fraudulent returns and mitigation strategies in multichannel retailing

The growth of online retailing has exceeded expectations over the last few years. This has resulted in high product return rates, which retailers are struggling with due to complex and costly returns processing, logistics, and financial implications. Additionally, online returns come with increased opportunities for returns fraud. During the pandemic, new types of returns fraud have emerged and returns fraud rates have increased across all channels. Based on a series of semi-structured interviews with retailers and retail experts, we investigate factors that enable fraudulent returns from consumers' and retailers’ perspectives and outline strategies for retailers to combat product returns fraud in a multichannel environment, leading to a framework for retail fraud. We contribute critical insights to research and practices on understanding and addressing a growing problem that has economic, social and environmental implications.

The Importance of Limited Self-Determination When M-Channel Migration Strategy Is Implemented

Theoretical background: Multichannel retailers can implement various migration strategies to induce consumers to use particular marketing channel. Some researchers indicated voluntary and forced customer E-channel migration strategies. Due to the negative consequences of a coercive strategy, a voluntary migration strategy is much more popular. Voluntary migration strategy provides multichannel shoppers a total freedom of their choice whereas the incentive-based migration strategy uses some stimulus in order to convince buyers to use specific marketing channel. Encouraging the buyer to behave in a particular way may cause him/her a negative self-determination perception. Limited self-determination means consumer conviction that a certain action was taken as a result of marketing initiatives, prompted by the seller, and is not the result of their free and independent decision. A self-determined customer is convinced of entering into a relationship with the provider on their own initiative. In the context of channel-based price differentiation, it is about the consumer's belief that a specific purchase channel has been selected as a result of a solicitation by the seller. According to researchers, limited self-determination can have potentially negative impact on the intention to buy. Purpose of the article: The presented research model refers to the customer intention to buy online (intention to stay there) in the multichannel context. Therefore, the aim of this paper is to contribute to existing literature on multichannel pricing and advance our understanding of factors influencing the customer intention to make a purchase in offline channel (to stay in a brick-and-mortar store) under the price pressure in mobile app. This study aims to investigate factors affecting the intention to purchase offline when m-channel migration strategy based on price incentives is implemented by the retailer. Special attention is devoted to the issue of limited self-determination in a channel-based price differentiation context. Research methods: The data comes from a questionnaire survey carried out in 2021. This study is a quantitative study employing a scenario-based approach. The total sample size is 500, cosmetics was the product category which the questionnaire was prepared for. For the purpose of the research, a SEM (Structural Equation Modelling) analysis using AMOS 26 was conducted. Main findings: This research extends the understanding of consumer limited self-determination and subjective knowledge and mobile app familiarity and its influence on the intention to buy offline when price incentives are provided in a mobile purchase app. Article adds to the existing literature on customer migration in a multichannel environment.

Implications of Online-Buying to Store-Pickup (O2S) for End-to-End Supply Chain Strategy

A growing body of literature examines the demand effects of the increasingly popular retailing strategies of integrating digital sales channels with brick-and-mortar stores, allowing customers to buy goods online and pick them up in a store (termed BOPS) or by the store’s curbside. Typically, however, implications of such strategies are explored for the retail channel alone while ignoring the sourcing strategy, which affects a key driver of their influence: product availability. We study such online-to-store (O2S) strategies using an analytical model of the end-to-end supply chain for two cases: a brick-and-mortar retailer expanding its market via O2S, and a retailer integrating its independent brick-and-mortar and online channels via O2S. We derive rational expectations equilibrium product availability, involving sourcing strategy and consumer choice, in pre and post-O2S cases to provide three insights about the interdependence of O2S and sourcing strategies. First, market expansion via O2S is moderated by the retailer’s sourcing strategy: it is achieved only if the equilibrium pre-O2S product availability is below a certain threshold. Second, introduction of an O2S strategy can affect the feasibility of retailer’s suppliers: it can render an existing supplier economically infeasible and make a previously-infeasible supplier feasible. Third, cost-efficient processing of goods returned by the retailer’s O2S and online consumers is necessary not just for retail profitability but also to ensure supplier feasibility. For practice, this highlights the need to plan the retail and sourcing strategies in a multi-channel environment jointly as interdependent components of an end-to-end supply chain. Managers are thus forewarned of pitfalls from separating the decision-making in retailing and sourcing strategies.

Assessing the Role of Traditional and New Media in a Multichannel Environment

The research which is conducted on the role of the new media and traditional in the multichannel environment has analyzed social media and advertising and their impact on the multicultural environment. The research also discusses the various activities that are intended in the marketing results. Moreover, the study has highlighted the importance of the traditional and new media and also evaluated their values in this modern world. However, the research also elaborated on the aims and the main objection of the research, which are the identification of the various models of the traditional and new media that are in the multichannel environment, also evaluate the role of new media and traditional, moreover discussing the benefits and advantages of the new media and traditional. In addition to this, this research has chosen the qualitative research approach in which the inductive approach has been discussed, and also the sample size that is included in the study is 100-120.

ANALYSIS OF BRAND POPULARITY USING BIG DATA AND TWITTER

Social media actions such as commenting, tweeting, liking and sharing can act as proxies for consumer’s attention to a particular product. In this paper, we demonstrate how social media data from Twitter can be used to analyse the popularity of a brand. We discuss such findings of brands like Apple, Samsung, Nike, Reebok, Amazon, Google, Sony, Panasonic, Fossil, Fastrack, using sentiment analysis. Human beings love to eat information. Information is how we come to make sense of the world. The philosopher Isaiah Berlin said, “To Understand Is to Perceive Patterns”. Carl Sagan says, “Understanding is a kind of ecstasy”. Today we are living in the age of Big Data. We are living in an age in which, we are producing more information than ever before, we are consuming more information than ever before, we are quantifying and making sense of more information than ever before, and it is leading to a revolution of human possibility. So what exactly does big data makes possible? In this paper, we analyse few brands, and to some extent their products, that have generated a large number of opinions on Twitter. We have chosen Twitter because; Twitter Data is the most comprehensive, participative, live public platform where key brands are discussed about, everyday. Data makes possible things we cannot even imagine, and in this paper we will be exploring precisely, the implication of this big data revolution. It is a new chapter in human possibility; it is a new chapter in what it means to be us. Our paper is associated with analysis from large amounts of big data using Sentiment Analysis. Today we analyze and collect data. Tomorrow we’ll be doing the inverse. We are on the verge of collecting data in almost every dimension of every organization which will enable us to look at data before we form questions. That means we’ll be getting answers to questions we didn’t know to ask. We will be reasserting before we assume things to be facts. For many company’s data is both their biggest asset and biggest challenge. It's the key to the understanding and engaging their consumer's. It lets them efficiently and effectively plan their product launch and successive releases. When it comes to the supply chain management data means visibility and flexibility at a global level, brands competing on low margins have known for decades that data is a powerful tool, and big data takes it and supercharges it for the modern multichannel environment. Company’s who embrace big data throughout their organization can unlock hidden value and many other functions as well. Shown below is the structure of this paper. Related work on predictive analytics is reviewed in the next section. Steps taken to analyze the brand popularity using Twitter data are mentioned in the third section. The results are tabulated in the fourth section. Further, the advantages of sentiment analysis and its applications are listed in the fifth section. Lastly, we have concluded and narrated the future scope that we wish to implement in our upcoming paper.

A cross layer based cooperative broadcast protocol for multichannel VANET

In multichannel environment of Vehicular Ad Hoc Network (VANET), the control channel (CCH) is exclusively dedicated for broadcast communication. Generally, immoderate transmission of packets has heightened the level of contention and collision at CCH, so a controlled flow is needed. The proposed Cross-Layer based Cooperative Broadcast Protocol (CLCBP) is designed to manage safety traffic at CCH, where a receiver-oriented MAC layer based prioritization scheme is used. A modified 2-D Markov chain model is achieved to theoretically investigate vehicle's queue's backoff procedure, where a density dependent dynamic contention window is shown as a convenient way to control collision. So, the collision density information from network layer is used to adjust the contention window at MAC layer. Additionally, a fuzzy logic technique is used to evaluate rebroadcast probability of receiver on the basis of its efficiency, collision density and packet's priority. In order to meet the delay constraint, the backoff slot duration for vehicles gets lowered with increasing value of rebroadcast probability. The simulation results show that the proposed scheme maintains a good balance between coverage delay, reachability, and saved rebroadcast in comparison with the other broadcast schemes.

Improvement of Multichannel LoRa Networks Based on Distributed Joint Queueing

LoRa has gained popularity in realizing IoT applications by facilitating long-range communication with low power consumption. However, LoRa faces scalability issues due to its unsophisticated random access (RA) protocol, Aloha, which is vulnerable to collision and not scalable in dense network scenarios. In contrast, distributed queuing (DQ), a collisionfree contention-based RA protocol, is a promising candidate for replacing Aloha because of its near-optimal performance and independence from the traffic load and pattern. However, DQ is not compatible with LoRa, as it was initially designed to operate on CableTV that supports the full-duplex (FDX) bidirectional link. In FDX, the contention feedback overhead is negligible. Most wireless networks, such as LoRa, support the half-duplex, for which feedback overhead is considerable. Furthermore, a reduction in efficiency is aggravated under a multi-channel environment because of an unbalanced traffic load. This study proposes a joint distributed queueing protocol to consider contention for LoRa that minimizes control overhead and achieves inter-channel load balancing. Our analysis shows that the proposed protocol reduces the control overhead by up to 70% compared to DQ. The protocol performance demonstrates near-optimum throughput and access delay, irrespective of the number of arrivals.