Results

Found 3 articles

Clear filters

The Application of Role-Based Framework in Preventing Internal Identity Theft Related Crimes: A Qualitative Case Study of UK Retail Companies
PDF
2023 | Information Systems Frontiers | Citations: 0
Authors: Okeke, Romanus Izuchukwu; Eiza, Max Hashem

Abstract: This paper aims to examine the challenges of preventing internal identity theft ... Expand

Abstract: This paper aims to examine the challenges of preventing internal identity theft related crimes (IIDTRC) in the UK retail sector. Using an in-depth multiple case studies of a selected number of cross-functional management teams in the UK retail companies, management roles were analysed. We used semi-structured interview as a qualitative data collection technique and used Nvivo aided thematic analysis and interpretivism underpinned by Role-Based Framework (RBF) for analysis. Our findings revealed that vagueness of roles and lack of clarity in sharing data security responsibilities are the major challenges of preventing IIDTRC in UK retail companies. We suggest an application of RBF which provides a conceptual analysis for cross-functional management team to address the challenges of preventing IIDTRC. RBF enables clarity of shared roles where both information security and crimes prevention teams work in unison is required to prevent IIDTRC to maximise internal data security. Contributions for policymakers are offered in this paper. Collapse

Semantic filters: organizational role theory

Topics: criminality data security IT security outsourcing IT security threat

Methods: case study qualitative interview personal interview survey qualitative content analysis

Theories: organizational role theory
Algorithms as co-workers: Human algorithm role interactions in algorithmic work
PDF
2023 | Information Systems Journal | Citations: 0
Authors: Tarafdar, Monideepa; Page, Xinru; Marabelli, Marco

Abstract: In algorithmic work, algorithms execute operational and management tasks such as ... Expand

Abstract: In algorithmic work, algorithms execute operational and management tasks such as work allocation, task tracking and performance evaluation. Humans and algorithms interact with one another to accomplish work so that the algorithm takes on the role of a co-worker. Human–algorithm interactions are characterised by problematic issues such as absence of mutually co-constructed dialogue, lack of transparency regarding how algorithmic outputs are generated, and difficulty of over-riding algorithmic directive – conditions that create lack of clarity for the human worker. This article examines human–algorithm role interactions in algorithmic work. Drawing on the theoretical framing of organisational roles, we theorise on the algorithm as role sender and the human as the role taker. We explain how the algorithm is a multi-role sender with entangled roles, while the human as role taker experiences algorithm-driven role conflict and role ambiguity. Further, while the algorithm records all of the human's task actions, it is ignorant of the human's cognitive reactions – it undergoes what we conceptualise as ‘broken loop learning’. The empirical context of our study is algorithm-driven taxi driving (in the United States) exemplified by companies such as Uber. We draw from data that include interviews with 15 Uber drivers, a netnographic study of 1700 discussion threads among Uber drivers from two popular online forums, and analysis of Uber's web pages. Implications for IS scholarship, practice and policy are discussed. Collapse

Semantic filters: organizational role theory

Topics: Uber mobile application ride sharing platform global navigation satellite system web page

Methods: computational algorithm qualitative interview qualitative coding netnography theory development

Theories: organizational role theory role theory
Perceived barriers to effective knowledge sharing in agile software teams
PDF
2016 | Information Systems Journal | Citations: 51
Authors: Ghobadi, Shahla; Mathiassen, Lars

Abstract: While the literature offers several frameworks that explain barriers to knowledg ... Expand

Abstract: While the literature offers several frameworks that explain barriers to knowledge sharing within software development teams, little is known about differences in how team members perceive these barriers. Based on an in-depth multi-case study of four software projects, we investigate how project managers, developers, testers and user representatives think about barriers to effective knowledge sharing in agile development. Adapting comparative causal mapping, we constructed causal maps for each of the four roles and identified overlap and divergence in map constructs and causal linkages. The results indicate that despite certain similarities, the four roles differ in how they perceive and emphasize knowledge-sharing barriers. The project managers put primary emphasis on project setting barriers, while the primary concern of developers, testers and user representatives were project communication, project organization and team capabilities barriers, respectively. Integrating the four causal maps and the agile literature, we propose a conceptual framework with seven types of knowledge-sharing barriers and 37 specific barriers. We argue that to bridge communication gaps and create shared understanding in software teams, it is critical to take the revealed concerns of different roles into account. We conclude by discussing our findings in relation to knowledge sharing in agile teams and software teams more generally. Collapse

Semantic filters: organizational role theory

Topics: knowledge sharing agile software development systems development Scrum IT workforce

Methods: qualitative interview design methodology cross sectional research personal interview mixed method

Theories: organizational role theory

Page 1 of 1

AIS11

Journals

Conferences

Semantic Filter

Found 3 articles

The Application of Role-Based Framework in Preventing Internal Identity Theft Related Crimes: A Qualitative Case Study of UK Retail Companies

Algorithms as co-workers: Human algorithm role interactions in algorithmic work

Perceived barriers to effective knowledge sharing in agile software teams