E-commerce channel management on the manufacturers’ side: ongoing debates and future research pathways

Since the beginning of the 2000s, online commerce has been gradually taking over and shaping the global marketplace. This has led several scholars to study the phenomenon from different angles, from consumer habits to privacy risks to related technological innovations. However, only recently has a branch of literature addressing the online channel management phenomenon from the manufacturers’ perspective emerged. This rapidly expanding literature strand remains rather fragmented, raising the need for a systematic literature review to comprehensively structure and discuss it. This study, accordingly, proposes a systematic literature review on online channel management from the manufacturers’ perspective. Firstly, it provides relevant bibliometric insights into the ongoing research on the topic. Secondly, applying the bibliographic coupling methodology individuates 92 interconnected contributions published by 31 December 2021. Three different, albeit interconnected, thematic clusters are discovered and reviewed, revealing their focus on (a) strategic marketing issues around manufacturervsretailer conflict, (b) pricing policies and trade-offs among pricevsservices, and (c) operational interactions and strategies between supply chain members. Finally, after a systematic literature review the authors develop thirteen original research propositions concerning new research pathways and theoretical advancements to be designed and implemented.

Using the UTAUT model to analyze user intention to accept electronic payment systems in Serbia

This study applies The Unified Theory of Acceptance and Use of Technology (UTAUT) to explain the acceptance of electronic payment systems in Serbia. We used extended model that incorporates several external variables, such as perceived security, trust, privacy, convertibility and financial costs, along with basic UTAUT predictors. The sample comprised of 457 respondents. We applied structural equation modelling to develop the model and draw conclusions. The results showed that performance expectancy, perceived security, trust and social influence had strong positive effects on behavioral intention. Conversely, we found behavioral intention, convertibility and financial costs to be significant drivers of user behavior. We consider the inclusion of convertibility in the model and proving its significance to be the main practical implications of our research, and also suggest to be considered as a factor in models designed for countries with low purchasing power of national currency.

The m15 Locus of Murine Cytomegalovirus Modulates Natural Killer Cell Responses to Promote Dissemination to the Salivary Glands and Viral Shedding

As the largest herpesviruses, the 230 kb genomes of cytomegaloviruses (CMVs) have increased our understanding of host immunity and viral escape mechanisms, although many of the annotated genes remain as yet uncharacterised. Here we identify the m15 locus of murine CMV (MCMV) as a viral modulator of natural killer (NK) cell immunity. We show that, rather than discrete transcripts from the m14, m15 and m16 genes as annotated, there are five 3′-coterminal transcripts expressed over this region, all utilising a consensus polyA tail at the end of the m16 gene. Functional inactivation of any one of these genes had no measurable impact on viral replication. However, disruption of all five transcripts led to significantly attenuated dissemination to, and replication in, the salivary glands of multiple strains of mice, but normal growth during acute infection. Disruption of the m15 locus was associated with heightened NK cell responses, including enhanced proliferation and IFNγ production. Depletion of NK cells, but not T cells, rescued salivary gland replication and viral shedding. These data demonstrate the identification of multiple transcripts expressed by a single locus which modulate, perhaps in a concerted fashion, the function of anti-viral NK cells.

Awaiting the Second Big Data Revolution: From Digital Noise to Value Creation

“Big data”—the collection of vast quantities of data about individual behavior via online, mobile, and other data-driven services—has been heralded as the agent of a third industrial revolution—one with raw materials measured in bits, rather than tons of steel or barrels of oil. Yet the industrial revolution transformed not just how firms made things, but the fundamental approach to value creation in industrial economies. To date, big data has not achieved this distinction. Instead, today’s successful big data business models largely use data to scale old modes of value creation, rather than invent new ones altogether. Moreover, today’s big data cannot deliver the promised revolution. In this way, today’s big data landscape resembles the early phases of the first industrial revolution, rather than the culmination of the second a century later. Realizing the second big data revolution will require fundamentally different kinds of data, different innovations, and different business models than those seen to date. That fact has profound consequences for the kinds of investments and innovations firms must seek, and the economic, political, and social consequences that those innovations portend.