The relative values of big data analytics versus traditional marketing analytics to firm innovation: An empirical study

2023 | Information & Management | Citations: 0

Authors: Cheng, Colin C.J.; Shiu, Eric C.

Abstract: Although big data analytics (BDA) does enhance innovation performance, it remain ... Expand

Abstract: Although big data analytics (BDA) does enhance innovation performance, it remains unclear whether BDA contributes more or less than traditional marketing analytics (TMA) to firm innovation. This study tests hy­ potheses based on data collected from multiple sources by using four-wave survey and archival data from 201 firms. The results indicate that BDA has a stronger positive effect on new product development (NPD) perfor­ mance than TMA, over time. However, TMA, when coupled with exploitative innovation strategy, has a stronger positive effect on NPD performance than if coupled with exploratory innovation strategy. Conversely, BDA, when coupled with exploratory innovation strategy, has a stronger positive effect on NPD performance than if coupled with exploitative innovation strategy. Collapse

Topics: innovation management analytical information system big data research and development marketing management

Methods: survey archival research partial least squares path modeling conceptual modelling Chow test

Theories: learning theory ambidexterity theory knowledge based theory of the firm

Corporate Hierarchy and Organizational Learning: Member Turnover, Code Change, and Innovation in the Multiunit Firm

2023 | Organization Science | Citations: 0

Authors: Joseph, John; Rhee, Luke; Wilson, Alex James

Abstract: This study examines how recombinant innovation is affected by member turnover an ... Expand

Abstract: This study examines how recombinant innovation is affected by member turnover and organizational learning within a corporate hierarchy. Prior work has overlooked the role of organizational structure in organizational learning, focusing instead on the knowledge provided by individual new hires or on the disruption caused by individual departures. We address this gap by applying March’s [March JG (1991) Exploration and exploitation in organizational learning. Organ. Sci. 2(1):71–87.] mutual learning model to a corporate hierarchy. In doing so, we theorize how the contributions of corporate staff to socializing new employees and to learning from the organizational code may differ from those of the organization’s subunit members. Empirically, we examine the learning effects of aggregate corporate and subunit arrivals and departures on novel recombinant innovation by subunits. Using 24 years of Motorola company directories, we construct membership turnover measures for corporate and subunit employees and exploit patent data to capture recombinant innovation. Our results suggest that, whereas the influx of new ideas through arrivals may be critical, breaking the pattern of inertial behavior through departures is more important for recombinant innovation. Corporate departures matter most for recombinant innovation, a result that reflects not only corporate staff’s slower individual learning from the organizational code but also its ability to update that code more quickly. In supplementary analyses, we find different effects for technical and nontechnical staff and internal and external arrivals, as well as demonstrate the mutual learning mechanism using internal corporate documents to capture code change. Our study has strong implications for theories of organizational learning, strategic human capital, organization design, and innovation. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2022.1618. Collapse

Topics: innovation management organization learning IT personell turnover global navigation satellite system communication service infrastructure

Methods: theory development statistical hypothesis test regression analysis method post-hoc analysis longitudinal research

Competitive Poaching in Search Advertising: Two Randomized Field Experiments

2022 | Information Systems Research | Citations: 0

Authors: Bhattacharya, Siddharth; Gong, Jing; Wattal, Sunil

Abstract: Keyword searches with brand names occur very commonly on search engines, enablin ... Expand

Abstract: Keyword searches with brand names occur very commonly on search engines, enabling firms to infer not only when consumers are searching for them but also when consumers are searching for their competitors. This enables firms to generate traffic from search advertising by bidding not only on their own keywords but also on competitors’ keywords. The strategy of bidding on competitors’ keywords, known as competitive poaching, presents unique opportunities for academic research. In this research, we examine the factors that influence the effectiveness of competitive poaching, specifically the role of different ad copies and the type of competitor (poached brand) from which a brand is poaching. We also examine how the presence of sponsored ads from the poached brand affects competitive poaching. We collected data from two randomized field experiments, one with a business school in the Northeastern United States and the other one with a leading automobile dealership company, where these firms bid on keywords of competing brands and randomly display different types of ad copies in the sponsored search listings. We find that, when poaching on keywords of high-quality brands, ad copies that feature vertical differentiation are more effective than the control ad copies, which do not convey any differentiation or prescriptive messages. We also find that when poaching from low-quality brands, ad copies featuring horizontal differentiation perform better than the control ad copies. Finally, we show that the presence of the poached brand’s own ad has a positive association with the ad effectiveness of the poaching brand when that poached brand is high quality and a negative association when the poached brand is low quality. The academic and managerial contributions are also discussed. Collapse

Topics: search engine search engine marketing vertical differentiation horizontal differentiation Google+

Methods: field experiment chi squared test experiment randomized field experiment Poisson regression

Calming the customers by AI: Investigating the role of chatbot acting-cute strategies in soothing negative customer emotions

2022 | Electronic Markets | Citations: 0

Authors: Zhang, Tao; Feng, Chao; Chen, Hui; Xian, Junjie

Abstract: Although intelligent chatbot has been widely used in online customer service set ... Expand

Abstract: Although intelligent chatbot has been widely used in online customer service settings in modern E-business, scholars still have little understanding of the chatbot strategies implemented in product or service failure context. Aiming at this gap, this study explored whether, how, and when two chatbot acting-cute strategies (i.e. whimsical chatbot strategy and kindchenschema chatbot strategy) could soothe negative customer emotions when product or service failure happened. By using two experimental studies, the results demonstrated that both the whimsical chatbot strategy and the kindchenschema (baby schema) chatbot strategy could placate negative customer emotions via two mechanisms. In the high product or service failure severity context, the soothing effects of both strategies would weaken, while the kindchenschema chatbot strategy weakens less. The whimsical chatbot strategy is suitable for customers with high technology anxiety while the kindchenschema chatbot strategy is suitable for those who have low technology anxiety. The whimsical chatbot strategy was more effective with male customers than with female customers, while the kindchenschema chatbot strategy had the opposite effect. Finally, the theoretical and managerial implications were discussed. Collapse

Topics: electronic business electronic commerce artificial intelligence user acceptance

Methods: chatbot experiment survey parametric test statistical hypothesis test

Making Digital Innovation Happen: A Chief Information Officer Issue Selling Perspective

2021 | Information Systems Research | Citations: 34

Authors: Chen, Daniel Qi; Zhang, Yanlin; Xiao, Jinghua; Xie, Kang

Abstract: Despite the large amount of touted benefits of digital innovation to contemporar ... Expand

Abstract: Despite the large amount of touted benefits of digital innovation to contemporary firms, scholarly attention to how digital innovation may take place within an organization is surprisingly limited. Drawing upon issue selling theory, this study examines how chief information officers (CIOs) could lead their organizations’ digital innovation initiatives. We propose that the CIO’s issue selling effectiveness, rather than his or her structural position, directly influences the level of organizational digital innovation success. Furthermore, the CIO’s structural power should not be overlooked because it could amplify (i.e., positively moderate) the impact of CIO issue selling to digital innovation outcomes. In addition, we identify four enabling forces of CIO issue selling effectiveness: (1) CIO strategic decision-making authority, (2) CIO/top management team partnership, (3) CIO information technologies (IT)–related strategic knowledge, and (4) CIO political savvy. Matched-pair survey data collected from senior business and IT executives of 179 organizations largely support the research hypotheses. The findings of the study suggest that issue selling perspective offers a powerful theoretical lens to examine CIO strategic impacts in the digital era. Collapse

Topics: Chief Information Officer innovation management digital innovation IT leadership decision making

Methods: survey instrumental variables estimation statistical hypothesis test causality analysis linear regression analysis

Work-Family Programs and Nonwork Networks: Within-Group Inequality, Network Activation, and Labor Market Attachment

2021 | Organization Science | Citations: 0

Authors: Ranganathan, Aruna; Pedulla, David S.

Abstract: Organizations increasingly offer work-family programs to assist employees with b ... Expand

Abstract: Organizations increasingly offer work-family programs to assist employees with balancing the competing demands of work and family life. Existing scholarship indicates that the consequences of work-family programs are heterogeneous across different socio-demographic groups, but limited research examines when and why workers within the same group may benefit differently from such programs. Understanding these differences may illuminate important mechanisms driving the effectiveness of work-family policies. We theorize that one key driver of within-group variation in the effectiveness of work-family programs is the extent to which workers’ nonwork social networks activate resources to support them. Specifically, we argue that workers whose nonwork networks are less likely to activate supportive resources will benefit more from organizational programs. We further posit that the status characteristics of workers’ dependents may shape the activation of resources among nonwork networks. Drawing on novel data from an Indian garment factory and a quasi-experimental research design, we examine how a work-family program, employer-sponsored childcare, affects the daily work attendance of a socio-demographically homogenous group of working mothers. We find that women whose nonwork networks are less likely to activate informal childcare support—specifically, women with daughters—benefit more from employer-sponsored childcare. Supplemental interview data supports our theoretical claims. We conclude by discussing the contributions of our argument to scholarship on work-family policies and social networks. Collapse

Topics: social network IT career logistics management missing data

Methods: qualitative interview Chow test quasi experiment descriptive statistic theory development

The Effects of Air Pollution and Sales Promotions on Channel Use across Online and Offline Retail

2020 | International Conference on Information Systems | Citations: 0

Authors: Jeong, Jaehoon; Lee, Dongwon; Gopal, Anand

Abstract: When the air quality is bad, people wear anti air pollution masks or restrict th ... Expand

Abstract: When the air quality is bad, people wear anti air pollution masks or restrict their outdoor activities. While this avoidance behavior is beneficial for the customers, it is unclear how air pollution affect other economic activities. We study how air pollution affects the relationship between offline and online sales associated with a retailer in Korea. This retailer offers regular promotion days monthly at both the offline and online channels. We test how air pollution affect the actual demand during these promotion days across the channels. Interestingly, air pollution significantly affects consumer behavior. In general, polluted air boosts online sales and promotion effectiveness. Unexpectedly, air pollution is unlikely to hurt the offline sales, and even increase offline sales and promotion effectiveness. We also find a notion of the inverted-U shaped reaction to the seriousness of polluted air in offline sales. These show the combined effect of channel substitution and recreational shopping. Collapse

Topics: climate change consumer behavior marketing management experience good information storage and retrieval system

Methods: Chow test robustness check data modeling

Evolutional and Transformational Configuration Strategies: A Rasch Analysis of IT Providers’ Service Management Capability

2020 | Journal of the Association for Information Systems | Citations: 0

Authors: Wulf, Jochen; Winkler, Till

Abstract: While providers of information technology (IT) services widely rely on reference ... Expand

Abstract: While providers of information technology (IT) services widely rely on reference models for IT service management (ITSM) practices, little is known about the actual configurations of these practices, referring to the patterns in which service providers adopt these practices at different maturity stages. We analyze how practice configurations reflect a provider’s ITSM capability and how this capability contributes to provider performance. This study addresses two gaps in the ITSM literature. First, empirical approaches to measuring a capability that manifests in configurations of ITSM practices and potentially different nonlinear configuration strategies are missing. Second, no theory explaining the resulting performance differences of alternative configuration strategies exists. We analyzed data from 315 IT service providers on the configuration of practices described in the widely regarded ITIL (formerly IT Infrastructure Library) reference model for ITSM. With this data, we conducted a Rasch calibration—a psychometric method for modeling latent traits based on noninterval scaled data—to measure practice maturity thresholds and providers’ ITSM capability on the same scale. Further, we regressed this measure of ITSM capability on service provider performance. Our findings contribute to the ITSM literature by uncovering two strategies for configuring ITSM practices with distinct capability scales. Drawing on prior theory, we characterize these as evolutionary and transformational configuration strategies. Service providers in the transformational class obtain higher performance gains from building ITSM capability than those in the evolutionary class. This supports our key argument that underlying practice complementarities are a key source of performance gains. Collapse

Topics: ITIL business process innovation innovation management IT service management anonymity

Methods: reference modelling survey regression analysis method theory development survey design

Off-The-Shelf Artificial Intelligence Technologies for Sentiment and Emotion Analysis: A Tutorial on Using IBM Natural Language Processing

2019 | Communications of the Association for Information Systems | Citations: 0

Authors: Carvalho, Arthur; Levitt, Adam; Levitt, Seth; Khaddam, Edward; Benamati, John

Abstract: Artificial intelligence (AI) rests on the premise that machines can behave in a ... Expand

Abstract: Artificial intelligence (AI) rests on the premise that machines can behave in a human-like way and potentially solve complex analytics problems. In recent years, we have seen several off-the-shelf AI technologies that claim to be ready to use. In this paper, we illustrate how one can use one such technology, called IBM Natural Language Understanding (NLU), to solve a data-analytics problem. First, we provide a detailed step-by-step tutorial on how to use NLU. Next, we introduce our case study in which we investigated the implications of Starbucks’ pledge to hire refugees. In this context, we used NLU to assign sentiment and emotion scores to social-media posts related to Starbucks made before and after the pledge. We found that consumers’ sentiment towards Starbucks became more positive after the pledge whereas investors’ sentiment became more negative. Interestingly, we found no significant relationship between consumers’ and investors’ sentiments. With help from NLU, we also found that consumers’ sentiments lacked consensus in that their social media posts contained a great deal of mixed emotions. As part of our case study, we found that NLU correctly classified the polarity of sentiments 72.64 percent of the time, an accuracy value much higher than the 49.77 percent that the traditional bag-of-words approach achieved. Besides illustrating how practitioners/researchers can use off-the-shelf AI technologies in practice, we believe the results from our case study provide value to organizations interested in implementing corporate social responsibility policies. Collapse

Topics: artificial intelligence Facebook social media application programming interface corporate social responsibility

Methods: sentiment analysis case study Cross-Industry Standard Process for Data Mining natural language processing regression analysis method

Information technology and innovation outcomes: is knowledge recombination the missing link?

2019 | European Journal of Information Systems | Citations: 18

Authors: Dong, John Qi; Yang, Chia-Han

Abstract: Firms’ use of information technology (IT) has been suggested to be an important ... Expand

Abstract: Firms’ use of information technology (IT) has been suggested to be an important enabler of knowledge production, leading to innovation outcomes in the form of patent inventions. However the innovation process through which IT use influences patent inventions is largely unclear. We draw on the knowledge recombination perspective and develop a model that explains the innovation process through which IT use influences innovation outcomes by looking into a firm’s efforts to recombine existing knowledge (i.e., knowledge recombinant intensity) and the scope of knowledge that is recombined by a firm (i.e., knowledge recombinant diversity). We also distinguish innovation outcomes in terms of patent quantity and quality. Using a large-scale panel dataset, we show that IT use has a stronger impact on knowledge recombinant intensity relative to knowledge recombinant diversity. Moreover, knowledge recombinant intensity and knowledge recombinant diversity play key mediating roles in the relationships between IT use and patent inventions. The impact of IT use on patent quantity is partially mediated, while the impact of IT use on patent quality is fully mediated. Our findings indicate that while IT use can directly affect patent quantity, its impact on patent quality must be channelled through a firm’s knowledge recombinant efforts and scope. Collapse

Topics: information system use innovation management digital innovation database system research and development

Methods: statistical hypothesis test theory development longitudinal research Compustat Granger causality