Search results

This paper aims to investigate the impact of three different flow channel cross sections on the performance of the fuel cell.

A comprehensive three-dimensional polymer electrolyte membrane fuel cell model has been developed, and a set of conservation equations has been solved. The flow is assumed to be steady, fully developed, laminar and isothermal. The investigated cross sections are the commonly used square cross section, the increasingly used trapezoidal cross section and a novel hybrid configuration where the cross section is square at the inlet and trapezoidal at the outlet.

The results show that a slight gain is obtained when using the hybrid configuration and this is because of increased velocity, which improves the supply of the reactant gases to the catalyst layers (CLs) and removes heat and excess water more effectively compared to other configurations. Further, the reduction of the outlet height of the hybrid configuration leads to even better fuel cell performance and this is again because of increased velocity in the flow channel.

The data generated in this study will be highly valuable to engineers interested in studying the effect of fluid cross -sectional shape on fuel cell performance.

This study proposes a novel flow field with a variable cross section. This design can supply a higher amount of reactant gases to the CLs, dissipates heat and remove excess water more effectively.

Cross-channel integration improves the operations of multi-channel and omnichannel marketing and increase firms' overall performance. By addressing the extant gaps in current literature, this configurational analysis aims to test the combined effects of organizational, channel and environmental factors on cross-channel integration.

Data were collected from a sample of 180 manufacturers. Necessary condition analysis (NCA) was used to test whether two organizational factors (firm size and IT capability), one environmental factor (environmental dynamism) and two channel factors (channel diversity and proportion of direct channels) were necessary or unnecessary conditions for high cross-channel integration. Fuzzy-set qualitative comparative analysis (fsQCA) was applied to analyze the configurational factors of high vs low cross-channel integration.

First, firm size and IT capability are non-linear and substitute for each other in affecting cross-channel integration in a diversified channel system with a high proportion of direct channels. Second, in a dynamic environment, firms with large size and IT advantage could achieve high cross-channel integration by diversifying channel types or increasing the proportion of direct channels. Third, the effect of channel diversity and proportion of direct channels on cross-channel integration is asymmetric depending on other antecedent conditions.

The authors tested a configurational framework developed from multiple theoretical perspectives. The authors' empirical findings contribute to the literature by providing insights into the mechanisms underlying the formation of high and low cross-channel integration. The results suggest multiple ways for firms to promote cross-channel integration by adjusting channel factors based on configurational conditions.

The purpose of this paper is to examine the role of consumer shopping orientations on consumer's channel choice, cross‐channel shopping behavior, and shopping outcomes.

Using multiple sources of data including surveys of store, web, and cross‐channel shoppers and their transaction information, the impact of consumer shopping orientations on comparison‐shopping, likelihood of cross‐channel usage, purchase outcomes including unplanned purchasing, retailer satisfaction, intent to return/abandon purchases, and share of category purchases are investigated.

Results suggest that high‐thrift customers patronizing a cross‐channel retailer are less likely to search for competitive offerings online or offline than customers patronizing a multiple channel retailer. Further, retailer satisfaction is higher for cross‐channel compared to multi‐channel retailers irrespective of the transaction channel used by consumers.

The data have external validity; however, they lack the control possible in laboratory experiments. Future research should examine if the findings can be replicated in multiple retail sectors.

These results suggest that brick‐and‐click retailers can exploit synergies between their channels through order online and pick up in store strategies for greater profitability than those who operate multiple independent channels.

This paper examines managerial implications of multiple independent channel vs cross‐channel strategies by retailers using data from customers of a commercial retailer.

The purpose of this study was to investigate whether consumers differ in their online or offline purchase intention, depending on which channel with price promotion information they are first exposed to, and to analyse the moderating role of brand trust.

Overall, 174 responses were obtained via an online survey using two contact channels (online/offline) by two levels of brand trust (high/low) between-subject designs.

Spillover effects were found across channels when a consistent price promotion is executed in both online and offline channels, purchase intentions for cross-channel and contact channel increase simultaneously. Although there was a similar effect in the discrepancy of purchase intentions towards the cross-channel according to contact channels, it varied depending on brand trust. When brand trust is high, having contact with offline price-discount information has a large online spillover effect. When brand trust is low, the spillover effect from online to offline is large.

This study expands the multi-channel research by proving the spillover effects between channels and confirming the difference according to brand trust.

Increasing promotion information for online contact is effective in driving offline visits for new brands, and the effective use of promotion information at offline stores can have a positive impact on online channels for well-known brands.

This study explores the cross-channel spillover effect of price promotion and proves that these effects depend on brand trust.

For consumers, cross-channel behaviour is increasingly prevalent. Such behaviour involves consumers actively engaging in (and deriving benefit) from one channel during a product search but switching to another channel when making a purchase. Drawing on multi-attribute utility theory, this study proposes a cross-channel behaviour typology consisting of three key aspects: channel choice behaviour, functional and economic outcomes and consumer-specific psychographic and demographic variables.

Segmentation analysis conducted via latent class analysis (LCA) was performed on a sample of 400 US consumers collected via an online survey.

Cross-channel behaviour is not always intentional. We identify a specific segment of consumers that most often engage in unplanned, rather than intentional, cross-channel switching. We find that of all shoppers that engage in cross-channel behaviour, a fifth (20%) are forced to switch channels at the point of purchase.

Cross-channel behaviour can be mitigated by retailers via a deep understanding of the driving factors of different configurations of showrooming and webrooming.

In contrast with existing conceptualisations, this study suggests that cross-channel behaviour often stems from consumers being “forced” by factors outside of their control, but within the retailers' control. This research presents a nuanced approach to decompose consumer cross-channel behaviour from the consumer perspective as planned, forced or opportunistic.

Research to date has yet to reach a consensus regarding the role of cross-channel consistency in omni-channel retailing. Therefore, this study aims to clarify the impact of cross-channel consistency on brand trust and loyalty by differentiating four dimensions of consistency (i.e. product, service, price and promotion consistency) and exploring the moderating roles of showrooming and webrooming motivation in these relationships.

A survey method is used to collect data. A total of 550 valid responses were obtained from multi-channel apparel brands' customers. Hypotheses were tested by employing structural equation modeling and hierarchical multiple regression analysis.

The results indicate that product and service consistency positively influence brand loyalty via brand trust, whereas price and promotion consistency do not. Furthermore, showrooming motivation negatively moderates the effects of service, price and promotion consistency on brand trust, while webrooming motivation positively moderates the effects of product, price and promotion consistency on brand trust.

This study contributes to the omni-channel retailing literature by examining the effects of different dimensions of cross-channel consistency and the moderating roles of showrooming and webrooming motivation to unravel the contradictions of previous studies. It reveals both the beneficial and dark sides of cross-channel consistency. It also extends the knowledge of brand building and cross-channel behavior in omni-channel retailing.

Purchasing behaviour across traditional retail and internet routes to market is becoming increasingly integrated. The positive and negative consequences of such behaviour for multi‐channel businesses have not been thoroughly examined – while an offline retail presence may reassure customers purchasing from an online channel, poor service online may negatively influence customer usage of an offline channel. This paper aims to address this issue.

A questionnaire survey of the online customers of four companies is employed and structural equation modelling used to investigate influences of demographic and behavioural variables (purchase involvement, loyalty, experience with the internet, company and product‐type) on positive and negative cross‐channel behaviour (CCB).

Strong evidence for both positive and negative customer CCB is found. Females, higher purchase involvement, higher loyalty and those with more experience of the company were more likely to display positive CCB; higher education, experience with the product type and online channel negatively influenced positive CCB. Increased age, education, occupation/class and purchase involvement lead to more negative CCB; product and company experience lead to reduced levels of negative CCB.

As a first step towards understanding of customer CCB the research generates many insights; however, more research is required to explore in more depth each of the constructs discussed and measured.

Understanding how different customer groups display different tendencies for CCB can help companies shape fulfilment and delivery strategies across different channels to market.

The study makes contributions to customer cross‐channel customer behaviour, developing implications for future research as well as management practice.

This study examines how retailers leverage multiple-channel strategies in relation to their customer value propositions (CVPs). More specifically, the purpose of this paper is to identify and analyze how multi-, cross- and omni-channel CVPs differ in terms of how they create value and which types of shopping motivations they aim to satisfy.

This conceptual paper presents and synthesizes three theoretical discussions pertaining to consumer shopping motivations, CVPs and multiple-channel retailing strategies into a tentative conceptual framework. Nine case examples are used to illustrate three different channel strategies: multi-channel, cross-channel and omni-channel retailing.

A tentative framework for understanding retailers’ channel strategies is suggested.

Retailers will benefit from a structured and synthesized understanding of the differences between multiple-channel strategies and their links to CVPs.

This paper introduces and integrates the concept of CVPs with the literature on multi-channel retailing strategies.

Over the last decade, technological and social trends have significantly influenced the relationship between customers and insurers. New buying patterns, price comparison platforms and the usage of different interaction channels driving single-product purchases and impacting lapses have influenced insurers’ customer portfolios and development. The purpose of this paper is to study the features driving the customer relationship along three areas, namely, customer acquisition, development and retention.

After defining 14 related hypotheses, the authors use econometric analyses to quantitatively support these hypotheses in the three areas of interest. The authors build on a large-scale longitudinal data set from a Swiss insurance company covering the period from 2005 to 2014 and including 2,757,000 customer-years. The data comprise information on private customers, their contract history, including coverage and losses and the channels used for buying insurance. This analysis focuses on the two most common non-life insurance products, namely, household/liability and car insurance.

The authors provide descriptive statistics and results from econometric analyses to determine the significant features and patterns affecting customer development and retention. Among the main results, the authors underline the significant influence on cross-selling given by the customer’s age and the interaction channel. Customers from rural regions are more loyal and likely to conduct cross-buying when compared to their peers from urban regions. Car insurance holders are more likely to lapse than household/liability insurance clients. Finally, while newly acquired customers tend to buy only a single product, the authors show the importance of cross-selling for retaining customers. In fact, customer retention is positively influenced by the number of products hold.

This work is relevant for academics and practitioners alike, adding a quantitative basis to the understanding of managing customer relationships and for the development of further prospective models. Further work could investigate or add products, extend the study to other companies and focus on customer development with time.

This study explores a large-scale longitudinal data set. The analyses of customer acquisition, development and retention can support insurers to construct their own models for customer relationship management.