The notion of ‘Big Data’ has recently been attracting an increasing degree of attention from scholars and practitioners in an attempt to identify how it may be leveraged to create innovative solutions and business opportunities. Specifically, Big Data may come from a variety of sources, especially sources outside the usual boundaries of organizations, and it represents an interesting and emerging opportunity for sustaining and enhancing the effectiveness of the so‐called open innovation paradigm. However, to the best of our knowledge, no prior works have provided a broad overview of the use of Big Data for open innovation strategies. We aim to fill this gap. In particular, we have focused our investigation on two types of companies: small and medium‐sized enterprises (SMEs) and big corporations, reviewing the major academic works published so far and analysing the main industrial applications on this topic. As a result, we provide a relevant list of the main trends, opportunities, and challenges faced by SMEs and large corporations when dealing with Big Data for open innovation strategies.
Purpose The purpose of this paper is to present a comprehensive picture of the innovative efforts undertaken over time to develop the digital technologies for managing the interface between supply chain management and marketing processes and the role they play in sustaining supply chain management-marketing (SCM-M) integration from an information processing point of view. Design/methodology/approach Patent analysis and actual examples are used to carry out this study. In detail, first, the authors identify the subset of enabling technologies pertaining to the fourth industrial revolution (Industry 4.0) that can be considered the most relevant for effective SCM-M integration (i.e. Industrial Internet of Things, Cloud computing, Big Data analytics and customer profiling, Cyber security). Second, the authors carry out a patent analysis aimed at providing a comprehensive overview of the patenting activity trends characterizing the set of digital technologies under investigation, hence highlighting their innovation dynamics and applications. Findings This research provides insightful information about which digital technologies may enable the SCM-M integration. Specifically, the authors highlight the role those solutions play in terms of information acquisition, storage and elaboration for SCM-M integration by relying on illustrative actual examples. Moreover, the authors present the organisations more involved in the development of digital technologies for SCM-M integration over time and offer an examination of their technological impact in terms of influence on subsequent technological developments. Originality/value So far, much has been said about why marketing and supply chain management functions should be integrated. However, a clear picture of the digital technologies that might be adopted to achieve this objective has yet to be revealed. Thus, the paper contributes to the literature on SCM-M integration and Industry 4.0 by highlighting the enabling technologies for the Industry 4.0 that may particularly serve for managing the SCM-M interface from an information processing perspective.
Purpose-This study proposes to model customer experience as a 'continuum', labelled Customer Experience Continuum (CEC). We adopt a customer experience quality construct and scale (EXQ) to determine the effect of customer experience on a bank's marketing outcomes. We discuss our study's theoretical and managerial implications, focusing on customer experience strategy design. Design/methodology/approach-We empirically test a scale to measure customer experience quality (EXQ) for a retail bank. We interview customers using a means-end-chain approach and soft-laddering to explore their customer experience perceptions with the bank. We classify their perceptions into the categories of 'brand experience' (pre-purchase), 'service experience' (during purchase), and 'post-purchase experience'. After a confirmatory factor analysis, we conduct a survey on a representative customer sample. We analyze the survey results with a statistical model based on the partial least squares method. We test three hypotheses: 1) Customers' perceptions of brand, service provider, and post-purchase experiences have a significant and positive effect on their experience quality (EXQ), 2) EXQ has a significant and positive effect on the marketing outcomes, namely share of wallet, satisfaction, and word-of-mouth, and 3) The overall effect of EXQ on marketing outcomes is greater than that of EXQ's individual dimensions. Practical implications-Banks should focus their customer experience (CE) strategies on the Customer Experience Continuum (CEC) and not on single encounters, tailoring marketing actions to specific stages in a customer's CE process. Different organisational units interacting with customers should be integrated into CE strategies, and marketing and communication budgets should be allocated according to CEC analysis. The model proposed in this paper enables the measurement of the quality of CE and its impact on marketing outcomes, thus enabling continuous improvement in customer experience. Findings-The results of the statistical analysis support the three hypotheses. Originality/value-The research proposes a different view of customer experience by modelling the interaction between company and customer as a continuum (CEC). It provides further empirical validation of the EXQ scale as a means of measuring customer experience. It also measures the impact of customer experience on a bank's marketing outcomes. It discusses the guidelines for designing an effective customer experience strategy in the banking industry.
Purpose The purpose of this paper is to explore how incumbents adapt their business models in response to digital innovation whose impact is either incremental or radical and source industry is either their own industry or other industries. The authors propose a conceptual matrix that is built on these two dimensions. Design/methodology/approach The authors build examples of four multinational incumbents operating in different sectors and known for their forefront approach to digital innovation to populate the matrix. Cases were chosen because of their polar nature that could provide variation in the two dimensions. The authors draw on a variety of qualitative secondary data sources to build the cases. Findings The study reveals how incumbents’ response to digital technologies (DTs) may differ depending on the resources or assets (including knowledge-based ones) that need mobilising. Business model changes and innovations may require full reconfiguration of a firm’s activity system; hence, one business model may be preferred to others depending on how burdensome the reconfiguration process will be. Research limitations/implications As the study is exploratory in nature, the anecdotal evidence provided in the paper are only some of the possible strategic responses of firms. Future studies may further into the dimensions the authors identified by empirically testing their validity with primary data. Practical implications The research offers managers and executives of incumbent firms a clear indication as to which elements of their business model ought to be adapted given the opportunities as well as the challenges brought about by DTs. Originality/value This research has explored incumbents’ response to DTs by primarily focusing on the nature and source industry of the underpinning innovation, besides any consideration of the drivers or processes that may lead to business model change.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
334 Leonard St
Brooklyn, NY 11211
Copyright © 2023 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.