Value Creation Tradeoff in Business Ecosystems: Leveraging Complementarities While Managing Interdependencies

2023 | Organization Science | Citations: 0

Authors: Agarwal, Shiva; Kapoor, Rahul

Abstract: Complementary assets play an important role in shaping an innovation’s commercia ... Expand

Abstract: Complementary assets play an important role in shaping an innovation’s commercialization success. In this paper, we broaden the locus of complementarities to examine the role of complementary technologies residing in the business ecosystems that are becoming an important source of value creation for innovating firms. We argue that, on one hand, complementary technologies help innovations create more value for their users. On the other hand, they can also limit the focal innovation’s value creation by exposing them to performance bottlenecks as the underlying technological architecture of the ecosystem evolves. We further extend the notion of specialization of complementary assets to ecosystems by considering complementary technologies that are specialized to a focal ecosystem and those that are available across multiple ecosystems. We highlight that, although the complementary technologies that are specialized to an ecosystem facilitate greater value creation, they are more likely to subject the focal innovation to performance bottlenecks. Evidence from 244,034 apps launched by software developers for Apple’s iPhone ecosystem during 2008–2015 offers strong support for our framework. In summary, the study sheds light on the value creation tradeoff for firms innovating in business ecosystems—the opportunities associated with leveraging complementarities and the challenges associated with managing technological interdependencies. Funding: S. Agarwal was funded by the McCombs School of Business at The University of Texas at Austin [Research Excellence Grant]. Collapse

Topics: mobile application innovation management value creation Apple iPhone iOS

Methods: statistical hypothesis test instrumental variables estimation cross sectional research proportional hazards model robustness check

The Power of Identity Cues in Text-Based Customer Service: Evidence from Twitter

2023 | Management Information Systems Quarterly | Citations: 0

Authors: Gao, Yang; Rui, Huaxia; Sun, Shujing

Abstract: Text-based customer service is emerging as an important channel through which c ... Expand

Abstract: Text-based customer service is emerging as an important channel through which companies can assist customers. However, the use of few identity cues may cause customers to feel limited social presence and even suspect the human identity of agents, especially in the current age of advanced algorithms. Does such a lack of social presence affect service interactions? We studied this timely question by evaluating the impact of customers' perceived social presence on service outcomes and customers' attitudes toward agents. Our identification strategy hinged on Southwest Airlines' sudden requirement to include a first name in response to service requests on Twitter, which enhanced customers' perceived level of social presence. This change led customers to become more willing to engage and more likely to reach a resolution upon engagement. We further conducted a randomized experiment to understand the underlying mechanisms. We found that the effects were mainly driven by customers who were ex ante uncertain or suspicious about the human identity of agents, and the presence of identity cues improved service outcomes by enhancing customers' perceived levels of trust and empathy. Additionally, we found no evidence of elevated verbal aggression from customers toward agents with identity cues, although a mechanism test revealed the moderating role of customers' emotional states. Our study highlights the importance of social presence in text-based customer service and suggests a readily available and almost costless strategy for firms: signal humanization through identity cues. Collapse

Topics: customer service Twitter social presence social media customer satisfaction

Methods: experiment computational algorithm synthetic control method survey support vector machine

Theories: social presence theory big five model

She? The Role of Perceived Agent Gender in Social Media Customer Service

2023 | International Conference on Information Systems | Citations: 0

Authors: Ke, Junyuan; Gao, Yang; Sun, Shujing; Rui, Huaxia

Abstract: This paper investigated the role of perceived agent gender in customer behavior ... Expand

Abstract: This paper investigated the role of perceived agent gender in customer behavior using a unique dataset from Southwest Airlines' Twitter account. We inferred agent gender based on the first names provided by agents when responding to customers. We measured customer behavior using three outcomes: whether a customer decided to continue the service conversation upon receiving an agent's initial response as well as the valence and arousal levels in their second tweet if the customer chose to continue the interaction. Our identification strategy relied on the Backdoor Criterion and hinged on the assumption that customer service requests are assigned to the next available agent, independent of agent gender. The findings revealed that customers were more likely to continue interactions with female agents than male agents and they were more negative in valence but less intense in arousal with the former group than with the latter. Collapse

Topics: Twitter customer service application programming interface Google+ service quality

Methods: word embedding computational algorithm machine learning support vector machine experiment

A Modular Social Sensing System for Personalized Orienteering in the COVID-19 Era

2023 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Pilato, Giovanni; Persia, Fabio; Ge, Mouzhi; Chondrogiannis, Theodoros; D’Auria, Daniela

Abstract: Orienteering or itinerary planning algorithms in tourism are used to optimize tr ... Expand

Abstract: Orienteering or itinerary planning algorithms in tourism are used to optimize travel routes by considering user preference and other constraints, such as time budget or traffic conditions. For these algorithms, it is essential to explore the user preference to predict potential points of interest (POIs) or tourist routes. However, nowadays, user preference has been significantly affected by COVID-19, since health concern plays a key tradeoff role. For example, people may try to avoid crowdedness, even if there is a strong desire for social interaction. Thus, the orienteering or itinerary planning algorithms should optimize routes beyond user preference. Therefore, this article proposes a social sensing system that considers the tradeoff between user preference and various factors, such as crowdedness, personality, knowledge of COVID-19, POI features, and desire for socialization. The experiments are conducted on profiling user interests with a properly trained fastText neural network and a set of specialized Naïve Bayesian Classifiers based on the “Yelp!” dataset. Also, we demonstrate how to approach and integrate COVID-related factors via conversational agents. Furthermore, the proposed system is in a modular design and evaluated in a user study; thus, it can be efficiently adapted to different algorithms for COVID-19-aware itinerary planning. Collapse

Topics: user satisfaction social network personality conversational agent Twitter

Methods: computational algorithm fastText machine learning experiment descriptive statistic

Improving scale adaptation practices in information systems research: Development and validation of a cognitive validity assessment method

2023 | Information Systems Journal | Citations: 1

Authors: Pillet, Jean-Charles; Carillo, Kevin D.; Vitari, Claudio; Pigni, Federico

Abstract: Scale adaptation, where authors alter the wording of an already published scale, ... Expand

Abstract: Scale adaptation, where authors alter the wording of an already published scale, is a deeply rooted social practice in IS research. This paper argues that the time is ripe to question this activity as well as the beliefs that have progressively formed around it. We identify and challenge five fallacious scale adaptation beliefs that hinder the development of more robust measure development norms. Contributing to this area of research, this paper offers a conceptual definition of the cognitive validity concept, defined as the extent to which a scale is free of problematic item characteristics (PICs) that bias the survey response process and subsequent empirical results. Building on this conceptualization effort, a new methodological process for assessing the cognitive validity of adapted IS measures is introduced. Through a series of three programmatic studies, we find converging evidence that the method can benefit the IS field by making the scale adaptation process more robust, transparent, and consistent. Along with the method, we introduce a new index that IS scholars can use to benchmark the cognitive quality of their scales against venerable IS measures. We discuss the implications of our work for IS research (including detailed implementation guidelines) and provide directions for future research on measurement in IS. Collapse

Topics: crowdsourcing privacy website evaluation criteria decision making

Methods: survey F-test parametric test literature study statistical hypothesis test

Executive AI Literacy: A Text-Mining Approach to Understand Existing and Demanded AI Skills of Leaders in Unicorn Firms

2023 | International Conference on Business Informatics | Citations: 0

Authors: Pinski, Marc; Hofmann, Thomas; Benlian, Alexander

Abstract: Despite the growing relevance of artificial intelligence (AI) for businesses, t ... Expand

Abstract: Despite the growing relevance of artificial intelligence (AI) for businesses, there is a lack of research on how top-level executives must be skilled in AI. Drawing on upper echelons theory, this paper explores executive AI literacy, defined as the combined AI skills of top-level executives, and its relevance for different executive roles. We conducted a text-mining analysis of 1,625 executives' online profiles and 1,033 executive job postings from unicorn firms retrieved via web-scraping from an online professional social network. We find that AI skills are mostly required in product-related executive roles (vs. administrative roles). Thus, we provide an AI-specific perspective complementing prior information systems research on executives, which asserts that (non-AI) IT is driven by administrative executive roles. Our paper contributes to AI literacy literature by shedding light on the substance of executive AI literacy within firms. Lastly, we provide implications for AI-related information systems strategy. Collapse

Topics: artificial intelligence marketing management social network IT skill IT job

Methods: natural language processing latent semantic analysis factor analysis term frequency–inverse document frequency topic model

Theories: upper echelons theory

A critical assessment of consumer reviews: A hybrid NLP-based methodology

2022 | Decision Support Systems | Citations: 0

Authors: Biswas, Baidyanath; Sengupta, Pooja; Kumar, Ajay; Delen, Dursun; Gupta, Shivam

Abstract: Online reviews are integral to consumer decision-making while purchasing product ... Expand

Abstract: Online reviews are integral to consumer decision-making while purchasing products on an e-commerce platform. Extant literature has conclusively established the effects of various review and reviewer related predictors to­ wards perceived helpfulness. However, background research is limited in addressing the following problem: how can readers interpret the topical summary of many helpful reviews that explain multiple themes and consecutively focus in-depth? To fill this gap, we drew upon Shannon’s Entropy Theory and Dual Process Theory to propose a set of predictors using NLP and text mining to examine helpfulness. We created four predictors - review depth, review divergence, semantic entropy and keyword relevance to build our primary empirical models. We also reported interesting findings from the interaction effects of the reviewer’s credibility, age of review, and review divergence. We also validated the robustness of our results across different product categories and higher thresholds of help­ fulness votes. Our study contributes to the electronic commerce literature with relevant managerial and theo­ retical implications through these findings. Collapse

Topics: online review electronic commerce computer virus protection information retrieval digital media

Methods: natural language processing robustness check term frequency–inverse document frequency topic model moderation analysis

Theories: dual-system theory chaos theory mathematical theory of communication elaboration likelihood model

Aligning adoption messages with audiences' priorities: A mixed-methods study of the diffusion of enterprise architecture among the US state governments

2022 | Information and Organization | Citations: 0

Authors: Bui, Quang Neo; Lyytinen, Kalle

Abstract: Prior studies on the diffusion of complex Information Systems (IS) innovations h ... Expand

Abstract: Prior studies on the diffusion of complex Information Systems (IS) innovations have leaned on the rhetoric of persuasion perspective to formulate rhetorical strategies that can persuade adopters to engage in adoption behaviors. Yet, most of them ignore the shifting priorities and changing identity of the audience. To address this gap, we extend the perspective by examining how in­ novators need to evolve the adoption message of an innovation by aligning it with the audience’s diverse and shifting priorities (and related identities). We trace rhetorical changes that the Na­ tional Association of State CIOs (NASCIO) introduced to promote the diffusion of enterprise ar­ chitecture (EA) between 2000 and 2012 among the 50 US states. We conduct a mixed methods analysis: first we qualitatively discern changes in the content of the rhetoric (message change); then we use a latent semantic analysis to measure the frame resonance between NASCIO’s shifting rhetoric and the audience’s changing priorities (alignment with audience priorities). Our findings highlight the importance of: 1) frame ambiguity that renders a complex IS innovation appealing to varied audiences over its diffusion trajectory; and 2) listening to the community members’ pri­ orities and aligning the adoption message with their dominant beliefs. Our analysis posits the rhetoric of identification as a complementary lens to account for the co-evolution of shared pri­ orities and identity alignments between innovators and their audiences. Collapse

Topics: innovation management Chief Information Officer digital innovation diffusion of innovation enterprise architecture

Methods: mixed method qualitative content analysis latent semantic analysis survey computational algorithm

Theories: co-evolution theory

Linking Exploits from the Dark Web to Known Vulnerabilities for Proactive Cyber Threat Intelligence: An Attention-Based Deep Structured Semantic Model

2022 | Management Information Systems Quarterly | Citations: 0

Authors: Samtani, Sagar; Chai, Yidong; Chen, Hsinchun

Abstract: Black hat hackers use malicious exploits to circumvent security controls and tak ... Expand

Abstract: Black hat hackers use malicious exploits to circumvent security controls and take advantage of system vulnerabilities worldwide, costing the global economy over $450 billion annually. While many organizations are increasingly turning to cyber threat intelligence (CTI) to help prioritize their vulnerabilities, extant CTI processes are often criticized as being reactive to known exploits. One promising data source that can help develop proactive CTI is the vast and ever-evolving Dark Web. In this study, we adopted the computational design science paradigm to design a novel deep learning (DL)- based exploit-vulnerability attention deep structured semantic model (EVA-DSSM) that includes bidirectional processing and attention mechanisms to automatically link exploits from the Dark Web to vulnerabilities. We also devised a novel device vulnerability severity metric (DVSM) that incorporates the exploit post date and vulnerability severity to help cybersecurity professionals with their device prioritization and risk management efforts. We rigorously evaluated the EVA-DSSM against state-of-theart non-DL and DL-based methods for short text matching on 52,590 exploit-vulnerability linkages across four testbeds: web application, remote, local, and denial of service. Results of these evaluations indicate that the proposed EVA-DSSM achieves precision at 1 scores 20% - 41% higher than non-DL approaches and 4% - 10% higher than DL-based approaches. We demonstrated the EVA-DSSM’s and DVSM’s practical utility with two CTI case studies: openly accessible systems in the top eight U.S. hospitals and over 20,000 Supervisory Control and Data Acquisition (SCADA) systems worldwide. A complementary user evaluation of the case study results indicated that 45 cybersecurity professionals found the EVADSSM and DVSM results more useful for exploit-vulnerability linking and risk prioritization activities than those produced by prevailing approaches. Given the rising cost of cyberattacks, the EVA-DSSM and DVSM have important implications for analysts in security operations centers, incident response teams, and cybersecurity vendors. Collapse

Topics: IT security web application information retrieval darknet PHP

Methods: computational algorithm case study experiment usability testing Okapi BM25

A growing or depreciating love? Linking time with customer satisfaction through online reviews

2022 | Information & Management | Citations: 1

Authors: Xu, Xun

Abstract: Through online customer reviews of hotels, this study examines the link between ... Expand

Abstract: Through online customer reviews of hotels, this study examines the link between time and customer satisfaction. We categorize the factors into different types, indicating that customers’ online review behavior and their level of satisfaction can change according to their duration of time with the service providers. Independent hotels and hotels with a higher star level, compared with chain hotels and hotels with a lower star level, amplify the in­ fluence of various attributes on satisfaction over time. We provide implications for firms to increase customer satisfaction by enhancing their attribute-level performance in various lengths of time. Collapse

Topics: customer satisfaction online review user-generated content logistics management website

Methods: parametric test Student's t-test term frequency–inverse document frequency logistic regression theoretical contribution