Pub Date : 2022-05-16DOI: 10.1080/12460125.2022.2074653
G. Birkbeck, Tadhg Nagle, David Sammon
ABSTRACT Driven by funding and publishing requirements to open and reuse data, Research Data Management (RDM) has become a crucial part of a researcher’s role. However, this key task is often completed by researchers, who sometimes make decisions, without having the necessary support or know-how, resulting in few research datasets being shared. The objective of this study is to identify the challenges in researcher RDM practices that impact the sharing/reusing of research data. Four thematic areas emerge from our coding of the selected literature: (i) alignment of research management and data management, (ii) resourcing, (iii) researcher openness, and (iv) research data governance. Despite the growing field of RDM, there is a limited understanding of RDM practiceshighlighting a requirement for further investigation together with practical tools, decision aids and training to assuage clearly unmet needs. Indeed, this provides an opportunity for the Information Systems (IS) community to better support researchers to implement good RDM practices.
{"title":"Challenges in research data management practices: a literature analysis","authors":"G. Birkbeck, Tadhg Nagle, David Sammon","doi":"10.1080/12460125.2022.2074653","DOIUrl":"https://doi.org/10.1080/12460125.2022.2074653","url":null,"abstract":"ABSTRACT Driven by funding and publishing requirements to open and reuse data, Research Data Management (RDM) has become a crucial part of a researcher’s role. However, this key task is often completed by researchers, who sometimes make decisions, without having the necessary support or know-how, resulting in few research datasets being shared. The objective of this study is to identify the challenges in researcher RDM practices that impact the sharing/reusing of research data. Four thematic areas emerge from our coding of the selected literature: (i) alignment of research management and data management, (ii) resourcing, (iii) researcher openness, and (iv) research data governance. Despite the growing field of RDM, there is a limited understanding of RDM practiceshighlighting a requirement for further investigation together with practical tools, decision aids and training to assuage clearly unmet needs. Indeed, this provides an opportunity for the Information Systems (IS) community to better support researchers to implement good RDM practices.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"153 - 167"},"PeriodicalIF":3.4,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47220756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-16DOI: 10.1080/12460125.2022.2073637
M. Walsh, John McAvoy, David Sammon
ABSTRACT The purpose of this review paper is to understand why organisations choose to implement data governance (DG) programmes. An understanding of these motivations will facilitate assessing the effectiveness of DG programmes. A search of the literature returned 628 publications for examination; of these 50 were deemed to be relevant to the research, and were selected for analysis and coding using a grounded theory approach. Our analysis found 115 organisational motivations for implementing DG, grouped into 23 categories. We use the Khatri and Brown framework to organise these categories across their five decision domains. The motivations are predominantly associated with operations and technology. This presents a challenge for organisations, where an over-focus on technology could lessen the business imperative. DG needs to be much more than an operational plan for managing the data asset. DG requires a holistic approach to succeed which suggests that all decision domains are considered adequately.
{"title":"Grounding data governance motivations: a review of the literature","authors":"M. Walsh, John McAvoy, David Sammon","doi":"10.1080/12460125.2022.2073637","DOIUrl":"https://doi.org/10.1080/12460125.2022.2073637","url":null,"abstract":"ABSTRACT The purpose of this review paper is to understand why organisations choose to implement data governance (DG) programmes. An understanding of these motivations will facilitate assessing the effectiveness of DG programmes. A search of the literature returned 628 publications for examination; of these 50 were deemed to be relevant to the research, and were selected for analysis and coding using a grounded theory approach. Our analysis found 115 organisational motivations for implementing DG, grouped into 23 categories. We use the Khatri and Brown framework to organise these categories across their five decision domains. The motivations are predominantly associated with operations and technology. This presents a challenge for organisations, where an over-focus on technology could lessen the business imperative. DG needs to be much more than an operational plan for managing the data asset. DG requires a holistic approach to succeed which suggests that all decision domains are considered adequately.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"282 - 298"},"PeriodicalIF":3.4,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45556253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-16DOI: 10.1080/12460125.2022.2070944
Viktor Andonovikj, P. Boškoski, Bojan Evkoski, Tjaša Redek, B. Mileva Boshkoska
ABSTRACT There is little evidence on the right approach on how to delineate the sub-networks in a labour market. The subject of research in this paper is computational influence identification of the labour force transitions between different professional occupations in the Slovenian labour network from 2010 to 2020. We use community detection algorithm to identify occupation groups and apply influence analysis on the Slovenian labour network from 2010 to 2020. This directly supports the decision-makers and employment services in identifying job opportunities for job-seekers based. The main conribution is using influence analysis to detect occupations and communities that had the most significant impact on the Slovenian labour market. The research is the first work to successfully apply community and influence analysis in the Slovenian labour network to the best of our knowledge. The paper carries several important implications, primarily highlighting the usage of existing data to increase employment levels.
{"title":"Community analysis in Slovenian labour network 2010-2020","authors":"Viktor Andonovikj, P. Boškoski, Bojan Evkoski, Tjaša Redek, B. Mileva Boshkoska","doi":"10.1080/12460125.2022.2070944","DOIUrl":"https://doi.org/10.1080/12460125.2022.2070944","url":null,"abstract":"ABSTRACT There is little evidence on the right approach on how to delineate the sub-networks in a labour market. The subject of research in this paper is computational influence identification of the labour force transitions between different professional occupations in the Slovenian labour network from 2010 to 2020. We use community detection algorithm to identify occupation groups and apply influence analysis on the Slovenian labour network from 2010 to 2020. This directly supports the decision-makers and employment services in identifying job opportunities for job-seekers based. The main conribution is using influence analysis to detect occupations and communities that had the most significant impact on the Slovenian labour market. The research is the first work to successfully apply community and influence analysis in the Slovenian labour network to the best of our knowledge. The paper carries several important implications, primarily highlighting the usage of existing data to increase employment levels.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"308 - 318"},"PeriodicalIF":3.4,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43961147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-16DOI: 10.1080/12460125.2022.2074650
Patrick McCarthy, David Sammon, Ibrahim Alhassan
ABSTRACT The objective of this theory-building research is to explore the defining characteristics of ‘doing’ Digital Transformation (DT) and present a holistic account of the practitioner practices that characterise ‘doing’ DT. For the purposes of this research ‘doing’ DT is defined as leveraging digital technologies to significantly alter an organisational design in order to enhance customer engagement. To fulfil this objective, we select 16 key informants (digital transformation leaders) based on their organisational perspective (Business or IT) and role (Strategic or Operational), which facilitates hearing 4 types of practitioner voices. Following an inductive open coding approach, 348 excerpts were coded, leading to the emergence of 95 concepts, which were further grouped into 14 categories. In this paper, we focus our write-up on the six most frequently occurring categories that are shaped by all four key informant groups (practitioner voices). This paper is unique in providing a holistic categorisation of the defining characteristics of ‘doing’ DT, while also providing 24 ‘Practitioner Priorities’. These ‘Practitioner Priorities’ sharpens the focus of academia and practice, highlighting the ‘role of people’, ‘role of data’ and ‘role of technology’ when ‘doing’ DT.
{"title":"‘Doing’ digital transformation: theorising the practitioner voice","authors":"Patrick McCarthy, David Sammon, Ibrahim Alhassan","doi":"10.1080/12460125.2022.2074650","DOIUrl":"https://doi.org/10.1080/12460125.2022.2074650","url":null,"abstract":"ABSTRACT The objective of this theory-building research is to explore the defining characteristics of ‘doing’ Digital Transformation (DT) and present a holistic account of the practitioner practices that characterise ‘doing’ DT. For the purposes of this research ‘doing’ DT is defined as leveraging digital technologies to significantly alter an organisational design in order to enhance customer engagement. To fulfil this objective, we select 16 key informants (digital transformation leaders) based on their organisational perspective (Business or IT) and role (Strategic or Operational), which facilitates hearing 4 types of practitioner voices. Following an inductive open coding approach, 348 excerpts were coded, leading to the emergence of 95 concepts, which were further grouped into 14 categories. In this paper, we focus our write-up on the six most frequently occurring categories that are shaped by all four key informant groups (practitioner voices). This paper is unique in providing a holistic categorisation of the defining characteristics of ‘doing’ DT, while also providing 24 ‘Practitioner Priorities’. These ‘Practitioner Priorities’ sharpens the focus of academia and practice, highlighting the ‘role of people’, ‘role of data’ and ‘role of technology’ when ‘doing’ DT.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"341 - 361"},"PeriodicalIF":3.4,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44412873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-16DOI: 10.1080/12460125.2022.2073864
M. Farkas, R. Matolay
ABSTRACT Decision support systems for corporate environmental management and ecological sustainability are proliferating, this paper explores their directions in a multifaceted literature via an integrative literature review. Besides delineating the interrelated areas of decision support systems for sustainability, we study the role of internal stakeholders in their implementation. In our review, we examine a relatively mature field (Environmental Decision Support System, EDSS) and an emerging field (Green Information System, Green IS), and their potential interplays. The importance of stakeholder inclusion in general, and the participation of end-users in the design and implementation of decision support systems, in particular, are analysed in the EDSS literature. The Green IS has a prospective future in decision support with its capacity to capture corporate environmental performance. Green IS literature, however, has just recently identified the significance of employee participation: barriers and potentials to engage employees have already been identified but still to be explored.
{"title":"Decision support for corporate sustainability: systems and stakeholders","authors":"M. Farkas, R. Matolay","doi":"10.1080/12460125.2022.2073864","DOIUrl":"https://doi.org/10.1080/12460125.2022.2073864","url":null,"abstract":"ABSTRACT Decision support systems for corporate environmental management and ecological sustainability are proliferating, this paper explores their directions in a multifaceted literature via an integrative literature review. Besides delineating the interrelated areas of decision support systems for sustainability, we study the role of internal stakeholders in their implementation. In our review, we examine a relatively mature field (Environmental Decision Support System, EDSS) and an emerging field (Green Information System, Green IS), and their potential interplays. The importance of stakeholder inclusion in general, and the participation of end-users in the design and implementation of decision support systems, in particular, are analysed in the EDSS literature. The Green IS has a prospective future in decision support with its capacity to capture corporate environmental performance. Green IS literature, however, has just recently identified the significance of employee participation: barriers and potentials to engage employees have already been identified but still to be explored.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"214 - 225"},"PeriodicalIF":3.4,"publicationDate":"2022-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48860843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-12DOI: 10.1080/12460125.2022.2073639
Andrej Bregar
ABSTRACT Data on past and current decisions can be utilised to enhance the decision-making process by automating decisions or making problem solving more intuitive. Data is either extracted from distributed sources and repositories, or obtained with the regression analysis from holistically assessed alternatives and human judgements. One of possible advanced approaches to encourage intuitive decision-making aims at inferring criteria weights of the decision model with regard to correlations between preferential parameters, in such a way that objective inner information on alternatives is consolidated with personal knowledge and experience. This is relevant because the task of specifying criteria weights is cognitively demanding and represents a key aspect of each decision model. The paper first discusses the notation and infrastructure to exchange decision models and handle preferential information underlying the mechanisms of indirect weight derivation. As the main contribution of the research, a method for the inference of criteria weights from veto-related information is proposed, with which selective strengths of veto degrees are calculated to compare the magnitudes of veto, while strengths of veto assessments are used to determine the influence of veto on the deterioration of rankings or categories into which alternatives are sorted, respectively. Strengths of non-compensatory veto criteria are then projected into compensatory weights. The experimental study reveals the characteristics of indirectly derived criteria weights and the influence of veto. Several quality factors are considered, such as the validity of weights, accuracy of results, richness of information and ability to discriminate conflicting alternatives. Weights are also compared to standard ROC and RS surrogate weights. The approach is generalised to both common decision-making problematics of ranking and sorting.
{"title":"Use of data analytics to build intuitive decision models – an approach to indirect derivation of criteria weights based on discordance related preferential information","authors":"Andrej Bregar","doi":"10.1080/12460125.2022.2073639","DOIUrl":"https://doi.org/10.1080/12460125.2022.2073639","url":null,"abstract":"ABSTRACT Data on past and current decisions can be utilised to enhance the decision-making process by automating decisions or making problem solving more intuitive. Data is either extracted from distributed sources and repositories, or obtained with the regression analysis from holistically assessed alternatives and human judgements. One of possible advanced approaches to encourage intuitive decision-making aims at inferring criteria weights of the decision model with regard to correlations between preferential parameters, in such a way that objective inner information on alternatives is consolidated with personal knowledge and experience. This is relevant because the task of specifying criteria weights is cognitively demanding and represents a key aspect of each decision model. The paper first discusses the notation and infrastructure to exchange decision models and handle preferential information underlying the mechanisms of indirect weight derivation. As the main contribution of the research, a method for the inference of criteria weights from veto-related information is proposed, with which selective strengths of veto degrees are calculated to compare the magnitudes of veto, while strengths of veto assessments are used to determine the influence of veto on the deterioration of rankings or categories into which alternatives are sorted, respectively. Strengths of non-compensatory veto criteria are then projected into compensatory weights. The experimental study reveals the characteristics of indirectly derived criteria weights and the influence of veto. Several quality factors are considered, such as the validity of weights, accuracy of results, richness of information and ability to discriminate conflicting alternatives. Weights are also compared to standard ROC and RS surrogate weights. The approach is generalised to both common decision-making problematics of ranking and sorting.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"31 - 49"},"PeriodicalIF":3.4,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47799625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-12DOI: 10.1080/12460125.2022.2073629
Julia Caulfield, A. Jha
ABSTRACT While we have seen many technological innovations in the way most sports are administered or played, stadium interaction had been largely unchanged till recently. However, with increasing technological intervention in stadiums, it is natural to ask questions on the initiatives that spectators prefer. This paper attempts to create a comprehensive study of such technological initiatives in modern stadiums across different sports. We have collected data from stadiums, categorised them and analysed spectator willingness to pay for these initiatives. We find that age and frequency of stadium visits are the most important characteristics that define the willingness of spectators to pay for high technology initiatives in stadiums. Our study is one of the few in the domain that presents both spectator and stadium side issues in enhancing digital initiatives in stadiums. It would enable future managers of stadiums to better plan and target right initiatives.
{"title":"Stadiums and Digitalization: An Exploratory Study of Digitalization in Sports Stadiums","authors":"Julia Caulfield, A. Jha","doi":"10.1080/12460125.2022.2073629","DOIUrl":"https://doi.org/10.1080/12460125.2022.2073629","url":null,"abstract":"ABSTRACT While we have seen many technological innovations in the way most sports are administered or played, stadium interaction had been largely unchanged till recently. However, with increasing technological intervention in stadiums, it is natural to ask questions on the initiatives that spectators prefer. This paper attempts to create a comprehensive study of such technological initiatives in modern stadiums across different sports. We have collected data from stadiums, categorised them and analysed spectator willingness to pay for these initiatives. We find that age and frequency of stadium visits are the most important characteristics that define the willingness of spectators to pay for high technology initiatives in stadiums. Our study is one of the few in the domain that presents both spectator and stadium side issues in enhancing digital initiatives in stadiums. It would enable future managers of stadiums to better plan and target right initiatives.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"331 - 340"},"PeriodicalIF":3.4,"publicationDate":"2022-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41362358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-11DOI: 10.1080/12460125.2022.2073634
P. Humphreys, Miguel Imas
ABSTRACT This paper offers a unique and powerful bottom-up methodology for social innovation promoting and securing Sustainable development goals (SDG’s) in a wide variety of social innovation contexts founded on a bottom-up approach : it identifies four sustainable development enabling factors, (SDEFs) that make social innovation contributions to sustainability in all its forms. We Employ three level (micro, meso, macro) model of social Innovation. In the first four sections of the paper, we show how the SDEF’s constitute social innovation success factors at the micro level, underpinning in ancient history, the enduing success of the Silk Road network of trade and, in recent history we reveal their role underpinning entrepreneurial innovation clusters bottom up. Yje concluding section shows how social innovation achievements implementing the SDEFs at the micro level can inform successful expansion into new contexts via adaptation and exaptation at the meso level and top-down facilitation at the macro level. .
{"title":"Decision support for social innovation enabling sustainable development","authors":"P. Humphreys, Miguel Imas","doi":"10.1080/12460125.2022.2073634","DOIUrl":"https://doi.org/10.1080/12460125.2022.2073634","url":null,"abstract":"ABSTRACT This paper offers a unique and powerful bottom-up methodology for social innovation promoting and securing Sustainable development goals (SDG’s) in a wide variety of social innovation contexts founded on a bottom-up approach : it identifies four sustainable development enabling factors, (SDEFs) that make social innovation contributions to sustainability in all its forms. We Employ three level (micro, meso, macro) model of social Innovation. In the first four sections of the paper, we show how the SDEF’s constitute social innovation success factors at the micro level, underpinning in ancient history, the enduing success of the Silk Road network of trade and, in recent history we reveal their role underpinning entrepreneurial innovation clusters bottom up. Yje concluding section shows how social innovation achievements implementing the SDEFs at the micro level can inform successful expansion into new contexts via adaptation and exaptation at the meso level and top-down facilitation at the macro level. .","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"181 - 201"},"PeriodicalIF":3.4,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47761293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-09DOI: 10.1080/12460125.2022.2073635
Aonghus Sugrue
ABSTRACT In 2017, the European Journal of Information Systems (EJIS) published an article titled ‘Stimulating dialog between information systems research and practice’. The genesis of this piece centred on the need for IS research to make practicable research insights accessible to practitioners and to provide a means for practitioners to ‘hear and be heard’. The resulting IT artefact – Science2Practice (now rebranded as AIS InPractice (AIP)) – presented a forum for researchers to have their academic publications summarised and published in practitioner ready insights. Almost 5 years on, this research looks to explore how the initiative supports its primary mission of communicating research to, and associated dialog with, practitioners through adopting a primary data collection via a systems investigation of the AIP website. The findings reveal a somewhat underwhelming artefact with opportunities missed to engage practitioners. Future research opportunities that could reinvigorate the AIP initiative are discussed.
{"title":"Build it, and they will come...Or will they?","authors":"Aonghus Sugrue","doi":"10.1080/12460125.2022.2073635","DOIUrl":"https://doi.org/10.1080/12460125.2022.2073635","url":null,"abstract":"ABSTRACT In 2017, the European Journal of Information Systems (EJIS) published an article titled ‘Stimulating dialog between information systems research and practice’. The genesis of this piece centred on the need for IS research to make practicable research insights accessible to practitioners and to provide a means for practitioners to ‘hear and be heard’. The resulting IT artefact – Science2Practice (now rebranded as AIS InPractice (AIP)) – presented a forum for researchers to have their academic publications summarised and published in practitioner ready insights. Almost 5 years on, this research looks to explore how the initiative supports its primary mission of communicating research to, and associated dialog with, practitioners through adopting a primary data collection via a systems investigation of the AIP website. The findings reveal a somewhat underwhelming artefact with opportunities missed to engage practitioners. Future research opportunities that could reinvigorate the AIP initiative are discussed.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"117 - 130"},"PeriodicalIF":3.4,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41750748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-06DOI: 10.1080/12460125.2022.2070951
Stefan Daschner, R. Obermaier
ABSTRACT There is empirical evidence that decision makers show negative behaviours towards algorithmic advice compared to human advice, termed as algorithm aversion. Taking a trust theoretical perspective, this study broadens the quite monolithic view on behaviour to its cognitive antecedent: cognitive trust, i.e. trusting beliefs and trusting intentions. We examine initial trust (cognitive trust and behaviour) as well as its development after performance feedback by conducting an online experiment that asked participants to forecast the expected demand for a product. Advice accuracy was manipulated by ± 5 % relative to the participant’s initial forecasting accuracy determined in a pre-test. Results show that initial behaviour towards algorithmic advice is not influenced by cognitive trust. Furthermore, the decision maker’s initial forecasting accuracy indicates a threshold between near-perfect and bad advice. When advice accuracy is at this threshold, we observe behavioural algorithm appreciation, particularly due to higher trusting integrity beliefs in algorithmic advice.
{"title":"Algorithm aversion? On the influence of advice accuracy on trust in algorithmic advice","authors":"Stefan Daschner, R. Obermaier","doi":"10.1080/12460125.2022.2070951","DOIUrl":"https://doi.org/10.1080/12460125.2022.2070951","url":null,"abstract":"ABSTRACT There is empirical evidence that decision makers show negative behaviours towards algorithmic advice compared to human advice, termed as algorithm aversion. Taking a trust theoretical perspective, this study broadens the quite monolithic view on behaviour to its cognitive antecedent: cognitive trust, i.e. trusting beliefs and trusting intentions. We examine initial trust (cognitive trust and behaviour) as well as its development after performance feedback by conducting an online experiment that asked participants to forecast the expected demand for a product. Advice accuracy was manipulated by ± 5 % relative to the participant’s initial forecasting accuracy determined in a pre-test. Results show that initial behaviour towards algorithmic advice is not influenced by cognitive trust. Furthermore, the decision maker’s initial forecasting accuracy indicates a threshold between near-perfect and bad advice. When advice accuracy is at this threshold, we observe behavioural algorithm appreciation, particularly due to higher trusting integrity beliefs in algorithmic advice.","PeriodicalId":45565,"journal":{"name":"Journal of Decision Systems","volume":"31 1","pages":"77 - 97"},"PeriodicalIF":3.4,"publicationDate":"2022-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46062805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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