Exploring the Implementation of a Legal AI Bot for Sustainable Development in Legal Advisory Institutions

This study explores the implementation of legal artificial intelligence (AI) robot issues for sustainable development related to legal advisory institutions. While a legal advisory AI Bot using the unique arithmetic method of AI offers rules of convenient legal definitions, it has not been established whether users are ready to use one at legal advisory institutions. This study applies the MCDM (multicriteria decision-making) model DEMATEL (decision-making trial and evaluation laboratory)-based Analytical Network Process (ANP) with a modified VIKOR, to explore user behavior on the implementation of a legal AI bot. We first apply DEMATEL-based ANP, called influence weightings of DANP (DEMATEL-based ANP), to set up the complex adoption strategies via systematics and then to employ an M-VIKOR method to determine how to reduce any performance gaps between the ideal values and the existing situation. Lastly, we conduct an empirical case to show the efficacy and usefulness of this recommended integrated MCDM model. The findings are useful for identifying the priorities to be considered in the implementation of a legal AI bot and the issues related to enhancing its implementation process. Moreover, this research offers an understanding of users’ behaviors and their actual needs regarding a legal AI bot at legal advisory institutions. This research obtains the following results: (1) It effectively assembles a decision network of technical improvements and applications of a legal AI bot at legal advisory institutions and explains the feedbacks and interdependences of aspects/factors in real-life issues. (2) It describes how to vary effective results from the current alternative performances and situations into ideal values in order to fit the existing environments at legal advisory institutions with legal AI bot implementation.

[1]  J. Fellous,et al.  Emotions: from brain to robot , 2004, Trends in Cognitive Sciences.

[2]  Charles J. Kacmar,et al.  Developing and Validating Trust Measures for e-Commerce: An Integrative Typology , 2002, Inf. Syst. Res..

[3]  David Yong Gun Fie,et al.  Adopting e-finance: decomposing the technology acceptance model for investors , 2015 .

[4]  Paul De Hert,et al.  Structuring modern life running on software. Recognizing (some) computer programs as new "digital persons" , 2018, Comput. Law Secur. Rev..

[5]  Chao-Min Chiu,et al.  Understanding e-learning continuance intention: An extension of the Technology Acceptance Model , 2006, Int. J. Hum. Comput. Stud..

[6]  Vicente Liern,et al.  A VIKOR-based approach for the ranking of mathematical instructional videos , 2019, Management Decision.

[7]  Chandra Prakash Garg,et al.  Sustainable outsourcing partner selection and evaluation using an integrated BWM–VIKOR framework , 2018, Environment, Development and Sustainability.

[8]  Jafar Rezaei,et al.  Ensemble ranking: Aggregation of rankings produced by different multi-criteria decision-making methods , 2020, Omega.

[9]  Chei Sian Lee,et al.  Understanding the Barriers to the Use of MOOCs in a Developing Country: An Innovation Resistance Perspective , 2019 .

[10]  Gwo-Hshiung Tzeng,et al.  Improving RFID adoption in Taiwan's healthcare industry based on a DEMATEL technique with a hybrid MCDM model , 2013, Decis. Support Syst..

[11]  Detmar W. Straub,et al.  Trust and TAM in Online Shopping: An Integrated Model , 2003, MIS Q..

[12]  Kung-Jeng Wang,et al.  Adopting robot lawyer? The extending artificial intelligence robot lawyer technology acceptance model for legal industry by an exploratory study , 2019, Journal of Management & Organization.

[13]  John O. McGinnis,et al.  The Great Disruption: How Machine Intelligence Will Transform the Role of Lawyers in the Delivery of Legal Services , 2014, Actual Problems of Economics and Law.

[14]  Changli Feng,et al.  Identification of the factors that influence service innovation in manufacturing enterprises by using the fuzzy DEMATEL method , 2020, Journal of Cleaner Production.

[15]  Arpita Khare,et al.  A meta-analysis of antecedents and consequences of trust in mobile commerce , 2020, Int. J. Inf. Manag..

[16]  Gwo-Hshiung Tzeng,et al.  Exploring mobile banking services for user behavior in intention adoption: using new hybrid MADM model , 2014, Service Business.

[17]  Izak Benbasat,et al.  Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation , 1991, Inf. Syst. Res..

[18]  Shirley Taylor,et al.  Decomposition and crossover effects in the theory of planned behavior: A study of consumer adoption intentions , 1995 .

[19]  Tommi Laukkanen,et al.  Consumer value creation in mobile banking services , 2005, Int. J. Mob. Commun..

[20]  Gwo-Hshiung Tzeng,et al.  Extended VIKOR method in comparison with outranking methods , 2007, Eur. J. Oper. Res..

[21]  Jin Baek Kim,et al.  An empirical study on consumer first purchase intention in online shopping: integrating initial trust and TAM , 2012, Electronic Commerce Research.

[22]  Trevor J. M. Bench-Capon,et al.  A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law , 2012, Artificial Intelligence and Law.

[23]  Chao-Che Hsu,et al.  A hybrid MCDM and sustainability-balanced scorecard model to establish sustainable performance evaluation for international airports , 2018, Journal of Air Transport Management.

[24]  L. Nora,et al.  Trust, commitment, and customer knowledge , 2019, Management Decision.

[25]  Dariusz Adamski,et al.  Lost on the digital platform: Europe’s legal travails with the Digital Single Market , 2018, Common Market Law Review.

[26]  Gwo-Hshiung Tzeng,et al.  Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS , 2004, Eur. J. Oper. Res..

[27]  Mary Lou Roberts,et al.  Technology vs. Consumer Behavior: The Battle for the Financial Services Customer , 1997 .

[28]  Tommi Laukkanen,et al.  Mapping the reasons for resistance to Internet banking: A means-end approach , 2007, Int. J. Inf. Manag..

[29]  Ashwani Kumar,et al.  Evaluating green performance of the airports using hybrid BWM and VIKOR methodology , 2020 .

[30]  Norman L. Chervany,et al.  What Trust Means in E-Commerce Customer Relationships: An Interdisciplinary Conceptual Typology , 2001, Int. J. Electron. Commer..

[31]  Chris Holder,et al.  Robotics and law: Key legal and regulatory implications of the robotics age (Part I of II) , 2016, Comput. Law Secur. Rev..

[32]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[33]  Mohammed Amin Almaiah.  Acceptance and usage of a mobile information system services in University of Jordan , 2018, Education and Information Technologies.

[34]  Stephen Castell.  The future decisions of RoboJudge HHJ Arthur Ian Blockchain: Dread, delight or derision? , 2018, Comput. Law Secur. Rev..