Customer models for artificial intelligence-based decision support in fashion online retail supply chains

2022 | Decision Support Systems | Citations: 0

Authors: Pereira, Artur M.; Moura, J. Antão B.; Costa, Evandro De B.; Vieira, Thales; Landim, André R.D.B.; Bazaki, Eirini; Wanick, Vanissa

Abstract: Fashion is a global, multi-trillion dollar industry devoted to producing and sel ... Expand

Abstract: Fashion is a global, multi-trillion dollar industry devoted to producing and selling clothing, footwear, and ac­ cessories to individuals or groups of people. Its sheer numbers, together with social and environmental sus­ tainability concerns, and the move towards digitalization of customer-centric operations, make the fashion business a prime target for Decision Support Systems (DSSs). On the other hand, decision support in fashion retail is particularly problematic and embraces all major supply chain domains. Decisions in an online fashion retail supply chain (FRSC) are highly dependent on time-varying customers' preferences and product availability, often leading to a combinatorial explosion. To address such a problem, DSSs could greatly benefit from high-quality information stored in customer models (CMs), constructed by using Artificial Intelligence techniques, allowing informed decisions on how to personalize (adapt) to match the customer's needs and preferences. Combinations of CMs with recommender systems (RSs) have been increasingly utilized in fashion e-commerce to provide personalized product recommendations. Nevertheless, works on enhancing CMs for e-commerce or other decision-making chain domains are scanty. This paper offers a systematic review of the literature on fashion CMs with applications to decision-making in FRSCs, mining topics for a research agenda. Research on the theme is relevant and urgent for the fashion business, which is still in its infancy. Work on the agenda topics could benefit distinct fashion stakeholders, not just customers, and produce well-grounded decision-making in varied FRSC contexts and dynamics. Collapse

Topics: artificial intelligence decision support decision making recommender system database system

Methods: structured literature research computational algorithm literature study machine learning literature sample

Interpersonal Relations and Social Actions on Live Streaming Services. A Systematic Review on Cyber-social Relations

2022 | HICSS | Citations: 0

Authors: Scheibe, Katrin; Zimmer, Franziska; Fietkiewicz, Kaja; Stock, Wolfgang

Abstract: This article provides a systematic review on interpersonal relations and social ... Expand

Abstract: This article provides a systematic review on interpersonal relations and social actions on live streaming services as, for instance, Twitch, Chaturbate, YouNow, or Taobao Live. Are those relations social, parasocial, or is there another specific kind of relation? Based on 77 articles, we give a short bibliometric overview and discuss interactions on live streaming services, social actions of streamers, social actions of viewers, shopping relations on live streaming services, and the streamers' and viewers' intentions to continuous actions leading (also supported by elements of gamification) the audience to a kind of stickiness towards individual streams, streamers, and services. Due to highly interactive communication between audience and broadcasters and among the viewers, social actions on live streaming services take a middle position between social and parasocial relations and-concerning shopping-also a middle position between physical eventshopping and ordering on an e-commerce platform. They form a new human-human relation, which we name "cyber-social relation." Collapse

Topics: streaming service video streaming service database system social media search engine

Methods: structured literature research literature sample meta analysis literature study bibliometric analysis

Opening organizational learning in crisis management: On the affordances of social media

2021 | Journal of Strategic Information Systems | Citations: 0

Authors: Eismann, Kathrin; Posegga, Oliver; Fischbach, Kai

Abstract: Research on the role of social media in crisis management has led to a deeper un ... Expand

Abstract: Research on the role of social media in crisis management has led to a deeper understanding of their affordances. This research, however, is fragmented, with a primary focus on crisis response. We lack a clear conceptualization of the affordances that social media offer by learning from them to prepare strategically for crises. Based on a systematic review of 128 papers, we inductively build a framework of social media affordances for organizational learning in crisis management. We discuss their role and interplay in strategic crisis management, focusing on organizational crisis learning, and outline avenues for future research based on this foundation. Collapse

Topics: social media organization learning emergency management affordance database system

Methods: structured literature research literature study literature sample digital trace data qualitative content analysis

Theories: theory of affordance organizational learning theory

A Multi-criteria Decision Support System for Ph.D. Supervisor Selection: A Hybrid Approach

2019 | HICSS | Citations: 0

Authors: Hasan, Mir Anamul; Schwartz, Daniel G

Abstract: Selection of a suitable Ph.D. supervisor is a very important step in a student’s ... Expand

Abstract: Selection of a suitable Ph.D. supervisor is a very important step in a student’s career. This paper presents a multi-criteria decision support system to assist students in making this choice. The system employs a hybrid method that first utilizes a fuzzy analytic hierarchy process to extract the relative importance of the identified criteria and sub-criteria to consider when selecting a supervisor. Then, it applies an information retrieval-based similarity algorithm (TF/IDF or Okapi BM25) to retrieve relevant candidate supervisor profiles based on the student’s research interest. The selected profiles are then re-ranked based on other relevant factors chosen by the user, such as publication record, research grant record, and collaboration record. The ranking method evaluates the potential supervisors objectively based on various metrics that are defined in terms of detailed domain-specific knowledge, making part of the decision making automatic. In contrast with other existing works, this system does not require the professor’s involvement and no subjective measures are employed. Collapse

Topics: information retrieval decision support system Elasticsearch database system systems implementation

Methods: Okapi BM25 computational algorithm survey term frequency–inverse document frequency trade-off analysis method

Understanding the Elephant: The Discourse Approach to Boundary Identification and Corpus Construction for Theory Review Articles

2019 | Journal of the Association for Information Systems | Citations: 51

Authors: Larsen, Kai R.; Hovorka, Dirk; Dennis, Alan; West, Jevin

Abstract: The goal of a review article is to present the current state of knowledge in a ... Expand

Abstract: The goal of a review article is to present the current state of knowledge in a research area. Two important initial steps in writing a review article are boundary identification (identifying a body of potentially relevant past research) and corpus construction (selecting research manuscripts to include in the review). We present a theory-as-discourse approach, which (1) creates a theory ecosystem of potentially relevant prior research using a citation-network approach to boundary identification; and (2) identifies manuscripts for consideration using machine learning or random selection. We demonstrate an instantiation of the theory as discourse approach through a proof-of-concept, which we call the automated detection of implicit theory (ADIT) technique. ADIT improves performance over the conventional approach as practiced in past technology acceptance model reviews (i.e., keyword search, sometimes manual citation chaining); it identifies a set of research manuscripts that is more comprehensive and at least as precise. Our analysis shows that the conventional approach failed to identify a majority of past research. Like the three blind men examining the elephant, the conventional approach distorts the totality of the phenomenon. ADIT also enables researchers to statistically estimate the number of relevant manuscripts that were excluded from the resulting review article, thus enabling an assessment of the review article's representativeness. Collapse

Topics: database system data quality accounting information system use usage intention

Methods: literature study computational algorithm machine learning literature sample theoretical contribution

Theories: technology acceptance model unified theory of acceptance and use of technology TAM2

BUSINESS PROCESS MODEL QUALITY – RESULTS FROM A STRUCTURED LITERATURE REVIEW

2018 | European Conference On Information Systems | Citations: 0

Authors: Dzepina, Aleksandra; Lehner, Franz

Abstract: ... Expand

Abstract: Collapse

Topics: database system business process management systems development data management web page

Methods: business process modeling literature study literature sample structured literature research conceptual modelling

Textual aggregation approaches in OLAP context: A survey

2017 | International Journal of Information Management | Citations: 3

Authors: Bouakkaz, Mustapha; Ouinten, Youcef; Loudcher, Sabine; Strekalova, Yulia

Abstract: In the last decade, OnLine Analytical Processing (OLAP) has taken an increasingl ... Expand

Abstract: In the last decade, OnLine Analytical Processing (OLAP) has taken an increasingly important role as a research field. Solutions, techniques and tools have been provided for both databases and data warehouses to focus mainly on numerical data. however these solutions are not suitable for textual data. Therefore recently, there has been a huge need for new tools and approaches that treat and manipulate textual data and aggregate it as well. Textual aggregation techniques emerge as a key tool to perform textual data analysis in OLAP for decision support systems. This paper aims at providing a structured and comprehensive overview of the literature in the field of OLAP Textual Aggregation. We provide a new classification framework in which the existing textual aggregation approaches are grouped into two main classes, namely approaches based on cube structure and approaches based on text mining. We discuss and synthesize also the potential of textual similarity metrics, and we provide a recent classification of them. Collapse

Topics: online analytical processing Microsoft Windows operating system hard disk drive programming language

Methods: machine learning computational algorithm survey literature sample literature study