Workforce management in omnichannel service centers with heterogeneous channel response urgencies

Ilk, Noyan; Brusco, Michael J.; Góes, Paulo

doi:10.1016/j.dss.2017.10.008

Cited by 20 publications

(8 citation statements)

References 30 publications

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“…In contrast, marketing‐focused studies placed a particular emphasis on channel management (Hosseini et al., 2018; Jocevski et al., 2019), product recommendation (Balakrishnan et al., 2018), pricing (Harsha et al., 2019), promotion (Blom et al, 2017) and sales management (Cummins et al., 2016). We only found a single study that focused on the area of human resource management, with particular attention to workforce management and scheduling decisions (Ilk et al., 2018).…”

Section: Research Findings and Analysismentioning

confidence: 99%

“…In terms of empirical studies on omnichannel retailing, most explored different functional areas of management, such as supply chain/logistics (Hübner et al, 2016b; Murfield et al., 2017; Paul et al., 2019; Song et al., 2019a; Yadav et al., 2019), marketing (Cao & Li, 2018; Hosseini et al., 2018; Jocevski et al., 2019; Picot‐Coupey et al., 2016; Shen et al., 2018; Zhang et al., 2018a), and to a lesser extent human resource management (Ilk et al., (2018). Along these lines, the majority of studies relied on data from multiple industries (Alexander & Cano, 2019; Buldeo Rai et al., 2019b; Jocevski et al., 2019; Larke et al., 2018; Saghiri et al., 2017; Valentini et al., 2020; Yrjölä et al., 2018a).…”

Section: Synthesis Of Findings and Future Research Agendamentioning

confidence: 99%

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Consumer decision‐making in omnichannel retailing: Literature review and future research agenda

Mishra

Singh

Köles

2020

Int J Consumer Studies

270

255

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The emergence of omnichannel retailing has revolutionized the way traditional e‐commerce business operates, subsequently bringing fundamental changes to consumer expectations and decision‐making processes. Despite the unquestionable relevance of this area of inquiry, the focal literature concerning omnichannel retailing remains sporadic and fragmented. With this in mind, the purpose of the current paper is to provide a comprehensive and concise state of the art literature review on omnichannel retailing. More specifically, we engage and draw upon the cognitive‐affective‐conative model to understand consumer behaviour within the omnichannel retailing context. The current study is built based on a review of total 131 research papers that were identified following a comprehensive search of the Web of Science database, capturing the time period between January 2011 and April 2020. This set of work was reviewed thoroughly to explore the aims, methodology and key contributions. In addition to engaging a systematic assessment and rigorous evaluation of the studies, we also extend literature by studying the relationship between omnichannel retailing and consumer decision making, with specific attention to consumer motivation, attitude and behaviour towards omnichannel retailing. Previous studies suggest consumer behaviour in omnichannel retailing to be a promising yet underexplored area with several potential avenues for future research. Among these, particularly lucrative directions include theory‐driven research, comparative cross‐cultural studies and qualitative approaches that capture rich first‐hand accounts of consumer decision‐making encounters. The current paper is timely and advantageous because it offers a holistic picture of omnichannel retailing research and provides literature‐driven evidence about a range of relevant consumer behavioural dimensions. It also integrates consumer responses using the cognitive‐affective‐conative model to advance our understanding of consumer decision‐making in the omnichannel customer journey. Recommendations for future research are provided using the Theory, Methodology and Context (TMC) framework. We conclude the paper by discussing implications for academics and practitioners.

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Section: Research Findings and Analysismentioning

confidence: 99%

Section: Synthesis Of Findings and Future Research Agendamentioning

confidence: 99%

Consumer decision‐making in omnichannel retailing: Literature review and future research agenda

Mishra

Singh

Köles

2020

Int J Consumer Studies

270

255

View full text Add to dashboard Cite

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“…Expanding on intra-firm considerations,Wiener et al (2018) conducted six case studies with three publishers and three retailers, which are running both online and offline business models simultaneously within the firm, to uncover synergies and tensions in value creation and capturing. Additionally, by embracing a phenomenon-driven comparative approach to conducting case studies, Wiener et al (2018) not only illustrated the pros and cons of having both online and offline business models co-existing within the firm, but they were also able to derive contextual factors that perpetuate or erode synergies and tension between the two business models.Type 2 (Retailer-Centric and Prescriptive):Prescriptive studies on retailer-centric issues related to omnichannel business have dealt primarily with how multichannel setup can be realized for retailers (e.g.,Ilk et al, 2018). Notably, omnichannel retailers are at aA C C E P T E D M A N U S C R I P Tdisadvantage when competing with pure online rivals due to the former's investment in physical infrastructure.…”

mentioning

confidence: 99%

Omnichannel business research: Opportunities and challenges

Chen

Cheung

Tan

2018

Decision Support Systems

109

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Detailing the opportunities and challenges of omnichannel business, this paper serves as an editorial note to the corresponding special issue. We advance a framework that delineates extant literature on omnichannel business into four predominant research streams according to perspective (i.e., consumer versus retailer) and research orientation (i.e., diagnostic versus prescriptive). For each of the four research streams, we articulate its current state of research and describe how select articles assembled in this special issue enhance the stream.

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“…At first, conversations were based only on e-mail protocols, which are standard today. However, there soon emerged chat, an entirely new contact channel that is being constantly developed [2]. According to studies of the C-SAT indicator [19], 73% of customers said they were satisfied with chat-based support.…”

Section: B Internet and Smartphonesmentioning

confidence: 99%

“…The current dynamic development of Contact Center (CC) systems puts increasing demands on companies that implement these types of products and on scientists who support the development of these technologies. CC system technologies have rapidly evolved from very simple Call Center type telecommunication concepts to multichannel, hybrid, largely automated, smart, and fully integrated Contact Center systems [1,2]. The changes taking place in CC systems are due to continuous efforts to optimize their internal processes, which translates directly into profits.…”

Section: Introductionmentioning

confidence: 99%

Influence of the Contact Center Systems Development on Key Performance Indicators

Płaza

Pawlik²

2021

IEEE Access

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The role played by information and communication technologies in human life is growing by the year. During the current pandemic, communication systems have become an essential part of operations of many industries around the world. This has also brought a dynamic development of solutions implemented in Contact Center systems, which ensure quick contact with customers. This paper presents how the pace of the development of Contact Center systems affects optimization of selected Key Performance Indicators (KPIs). It contains a detailed analysis of how successive technologies deployed in the industry, including IVR, chat, WebRTC, Visual IVR, Social Media, MultiChannel, OmniChannel and bots, have affected KPIs. The authors selected essential indicators that are critical to customer service, namely Service Level, Cost per Contact, Customer Satisfaction, Average Handle Time, First Call Resolution, Abandon Rate, Average Waiting Time, and Occupancy Rate. The authors also presented possible trends in the development of the solutions discussed in this paper, including in particular broad possibilities of employing artificial intelligence. AI methods will soon enable equipping Contact Centers with mechanisms for multi-criteria content classification and smart emotion recognition and behavioral profiling methods, and will optimize the process of predicting both inbound and outbound traffic.

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Workforce management in omnichannel service centers with heterogeneous channel response urgencies

Cited by 20 publications

References 30 publications

Consumer decision‐making in omnichannel retailing: Literature review and future research agenda

Consumer decision‐making in omnichannel retailing: Literature review and future research agenda

Omnichannel business research: Opportunities and challenges

Influence of the Contact Center Systems Development on Key Performance Indicators

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