Unrevealing the Dynamic Impact of Extended Reality Adoption on Offline Channel Performance

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Fang, Jie; Xiong, Bingqing; Li, Wilson; Song, Xiaofei

Abstract: The substantial attention of extended reality (XR) technology poses challenges ... Expand

Abstract: The substantial attention of extended reality (XR) technology poses challenges for multichannel retailers. On the one hand, retailers' adoption of XR can enhance consumers' online shopping experience and stimulate their purchases. On the other hand, XR technology replace the necessity for multichannel retailers to operate physical stores, which reflects the need to optimize channel structures while adopting XR. To ascertain how the multichannel retailers can outperform under such circumstances, this study combines the data sources of online website information and offline transaction information for over 1,100 global multichannel retailers from 2018 to 2022, thus involves 13497 monthly-brand observations. By using the fixed-effects model, the current study found that XR adoption duration has a non-linear impact on offline store conversion rate, which can initially increase customers' purchase decision in offline stores, but then turns to result in the negative impacts. Moreover, there are nuanced effects for XR with and without the affordance of create-ability. Findings of the paper aims to provide managerial implications for multichannel retailers to optimize channel structure and adopt XR technology for creating positive cross-channel synergy. Collapse

Topics: user experience technology adoption website information system use database system

Methods: Mann Whitney U test nonparametric test instrumental variables estimation difference in differences statistical hypothesis test

Theories: theory of affordance

Introduction to the Minitrack on GIS, Industry 4.0, and Sustainability

2023 | HICSS | Citations: 0

Authors: Shin, Namchul; Farkas, Daniel

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Methods: spatial analysis vehicle routing problem geographic analytics

Disintermediation and Its Mitigation in Online Two-sided Platforms: Evidence from Airbnb

2022 | International Conference on Information Systems | Citations: 0

Authors: Lin, Jinan; Nian, Tingting; Foutz, Natasha

Abstract: Disintermediation, where providers and customers transact bypassing an intermed ... Expand

Abstract: Disintermediation, where providers and customers transact bypassing an intermediary, has challenged the business model and dwindled profits of the multi-billion-dollar platform economy. Despite the platforms' efforts to mitigate disintermediation, little is known regarding the extent of disintermediation or efficacy of the mitigation policies, largely due to unobservability of disintermediation. We tackle these challenges by designing a geo-analytic methodology to identify and quantify disintermediation by matching online Airbnb booking and offline granular mobile location data. We further leverage DID with matching samples to causally examine the efficacy of four Airbnb policies; and finally propose a cost-and-benefit conceptual framework to interpret the findings and guide platform designs of mitigation policies. We find, for instance, a 5.4% of disintermediation in Austin, TX over Summer 2019; and Instant Bookable reduces disintermediation by 9%, with a stronger effect among the hosts without preference for long-term lease, with more repeated guests, and more hosting experience. Collapse

Topics: Airbnb geographic information system big data sharing platform Vrbo

Methods: experimental group geographic analytics propensity score matching robustness check topic model

Theories: transaction cost economics

Introduction to the HICSS-55 Minitrack on GIS, Industry 4.0, and Sustainability

2022 | HICSS | Citations: 0

Authors: Shin, Namchul; Farkas, Dan

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Methods: geographic analytics

Location Intelligent IS: GIS Decision-making and GISc Innovations

2022 | Americas Conference on Information Systems | Citations: 0

Authors: Sreedharan, Jayashree; Franklin, Dr CG

Abstract: Enhancing an IS (Information System) with GIS (Geographic Information System) d ... Expand

Abstract: Enhancing an IS (Information System) with GIS (Geographic Information System) decision-making software creates, manipulates, compares, and analyzes high resolution, spatial-temporal data-events like sales and census data on digital maps that improve the customer value chain. When this robust GIS insight (i.e., WHO is involved, WHAT the consequences are, WHEN events occur, WHERE events occur, and perhaps WHY events occur) is fused with a rigorous theoretical foundation in GISc (Geospatial Information Sciences) and other disciplinary theory and knowledge, the IS becomes a powerful predictor of demand chain management challenges and opportunities related to Marketing, Sales and Service. The paper demonstrates these linkages for the benefit of IS practitioners interested in understanding the effects of such an IS enhancement. Research questionWith the wide application and success of GIS implementations supporting IS supply chain management (SCM) applications e.g., the pulp and paper industry in New Brunswick, Canada (Killham & Morrison 2018), this paper seeks to investigate the following question:• What benefits can GIS decision-making and GISc innovations create with a location intelligent IS demand chain management (DCM) approach?Other questions for future research might include: If subtle changes are detected through the GIS decisionmaking and GISc innovations for the DCM, do those create timely opportunities for pivots or corrections in the SCM management functions (see Figure 2) i.e., Purchasing, Manufacturing and Distribution?.A physical/geographic analog (i.e., a topographical hill - Figure 1) is used to visualize the concepts. The conceptual model views the IS "hill" (ISH) as a stratified hierarchy structure in the "landscape" of supply and demand. The back-side (left) of the ISH represents all of the supply chain management functions -Purchasing, Manufacturing and Distribution. The front-side (right) of the ISH (the focus of this investigation), represents all the demand chain management functions of Marketing, Sales and Service (Figure 2). Collapse

Topics: diffusion of innovation marketing management innovation management decision making value creation

Methods: longitudinal research time series analysis geographic analytics

Information Systems Business Analytics Curriculum – Competencies from National Infocomm Skills Model and Job Listings

2021 | Americas Conference on Information Systems | Citations: 0

Authors: Gottipati, Swapna; Shankararaman, Venky; Shim, Kyong Jin; Yip, Chan Yuen

Abstract: To the best of our knowledge, no research has examined how to integrate the nat ... Expand

Abstract: To the best of our knowledge, no research has examined how to integrate the national skills model with the industry demand for designing business analytics curricula. To answer this question, we took the initial steps of identifying the job roles and skills required by the nation in "Data" domain. We then collected the skills that are required by business analytics job positions listed by industry. Further, we extracted the top tools, technologies, and programming languages (TTP) demanded by the industry for various categories of technical skills. We then combined the analyses to design the curriculum, courses, and content for various job roles for Information Systems graduates. Our results show that soft skills, technical skills, and TTP skills vary across different job roles. This study will help curriculum managers understand how to design a curriculum based on the national manpower skills needs aligned to the specific industry demands. Collapse

Topics: IT skill analytical information system soft skill IT career data governance

Methods: geographic analytics machine learning qualitative content analysis

Theories: socio technical theory

Reducing Transport Miles Through the Use of Mobile Hubs: A Case Study in Local Food Supply Chains

2021 | HICSS | Citations: 0

Authors: Sanders, Isabella T; Montreuil, Benoit

Abstract: Though environmentally friendly in many regards, local supply chains are often i ... Expand

Abstract: Though environmentally friendly in many regards, local supply chains are often inefficient due to lack of proper infrastructure. This paper explores the use and placement of mobile hubs for consolidation and distribution of goods in local supply chains. Specifically, we look at local food supply chains where food typically travels from rural farms to suburban and urban restaurants. Currently, consolidation is minimal and not optimized in these supply chains. This paper computes suitability and location analysis through a novel multi-criterion scoring methodology utilizing kernel density and network analysis. The effectiveness of these mobile hubs is assessed through strategic routing, where the routes are optimized for time and distance. Results indicate that on average mobile hubs do in fact reduce mileage and number of stops, lessening emissions in addition to saving time and money. The proposed methodology can be implemented in other local supply chains to better consolidate and distribute goods. Collapse

Topics: supply chain management logistics information system geographic information system internet technology logistics management

Methods: network analysis literature study computational algorithm spatial analysis optimization model

Predicting Store Closures Using Urban Mobility Data and Network Analysis

2021 | International Conference on Information Systems | Citations: 0

Authors: Shoshani, Tal; Zubcsek, Peter Pal; Reichman, Shachar

Abstract: In this paper, we show how retailers can use consumer mobility data to assess t ... Expand

Abstract: In this paper, we show how retailers can use consumer mobility data to assess the relative performance of each store within their network. We use mobile location data from over 5M devices in Manhattan, NY to construct a weighted network of Starbucks stores as nodes, with the edge weights between any two stores reflecting both the overlap between the customers of as well as the distance between the stores. We then compute network centrality measures to capture consumption dynamics in the network. Finally, we employ these variables to train machine learning models predicting whether or not each store closed down during the 20 months following our observation period. Our findings indicate that including network centrality measures derived from urban mobility data using our methods can lead to a better identification of underperforming stores in a retailer's network, revealed by subsequent store closure decisions. Collapse

Topics: geographic information system shapley additive explanation Google+ pandemic financial performance

Methods: machine learning computational algorithm gradient boosting geographic analytics logistic regression

Theories: game theory marketing theory

Public decision support for low population density areas: An imbalance-aware hyper-ensemble for spatio-temporal crime prediction

2019 | Decision Support Systems | Citations: 0

Authors: Kadar, Cristina; Maculan, Rudolf; Feuerriegel, Stefan

Abstract: Crime events are known to reveal spatio-temporal patterns, which can be used for ... Expand

Abstract: Crime events are known to reveal spatio-temporal patterns, which can be used for predictive modeling and subsequent decision support. While the focus has hitherto been placed on areas with high population density, we address the challenging undertaking of predicting crime hotspots in regions with low population densities and highly unequally-distributed crime. This results in a severe sparsity (i. e., class imbalance) of the outcome variable, which impedes predictive modeling. To alleviate this, we develop machine learning models for spatio-temporal prediction that are specifically adjusted for an imbalanced distribution of the class labels and test them in an actual setting with state-of-the-art predictors (i. e., socio-economic, geographical, temporal, meteorological, and crime variables in fine resolution). The proposed imbalance-aware hyper-ensemble increases the hit ratio considerably from 18.1% to 24.6% when aiming for the top 5% of hotspots, and from 53.1% to 60.4% when aiming for the top 20% of hotspots. As direct implications, the findings help decision-makers in law enforcement and contribute to public decision support in low population density regions. Collapse

Topics: criminality decision support predictive policing open data decision support system

Methods: machine learning random forest classification experiment ensemble learning computational algorithm

Theories: social disorganization theory

Continued Usage and Location Disclosure of Location-Based Applications: A Necessity for Location Intelligence

2019 | HICSS | Citations: 0

Authors: Koohikamali, Mehrdad; Mousavizadeh, Mohammadreza; Mousavizadeh, M; Peak, Dan

Abstract: Location-based applications (LBA) have been widely accepted and used for differe ... Expand

Abstract: Location-based applications (LBA) have been widely accepted and used for different purposes ranging from navigation to dating or gaming. Most LBAs ask users to provide access to location data for more efficient and personalized location-based services. Location intelligence as an emerging area of business intelligence relies heavily on disclosing location information by users. This research builds a continuance usage and location disclosure model from the expectation-confirmation perspective. The effect of benefit expectations on usefulness and satisfaction is hypothesized. In addition, the positive effect of usefulness on satisfaction and continuance intention is postulated. After collecting survey data from main LBA users, the results of the analysis support the proposed model. Findings contribute to the current literature in business intelligence by focusing on location disclosure behavior in the context of LBAs and the necessity of this type of information for location intelligence. Collapse

Topics: usage intention mobile application perceived usefulness personalization usability

Methods: survey partial least squares regression factor analysis geographic analytics descriptive statistic

Theories: expectation confirmation theory technology acceptance model post acceptance model