The role of artificial intelligence in understanding the strategic decision-making process

1991 ◽  
Vol 3 (2) ◽  
pp. 149-159 ◽  
Author(s):  
W.E. Spangler
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maqsood Ahmad ◽  
Syed Zulfiqar Ali Shah ◽  
Yasar Abbass

PurposeThis article aims to clarify the mechanism by which heuristic-driven biases influence the entrepreneurial strategic decision-making in an emerging economy.Design/methodology/approachEntrepreneurs' heuristic-driven biases have been measured using a questionnaire, comprising numerous items, including indicators of entrepreneurial strategic decision-making. To examine the relationship between heuristic-driven biases and entrepreneurial strategic decision-making process, a 5-point Likert scale questionnaire has been used to collect data from the sample of 169 entrepreneurs who operate in small- and medium-sized enterprises (SMEs). The collected data were analyzed using SPSS and Amos graphics software. Hypotheses were tested using structural equation modeling (SEM) technique.FindingsThe article provides empirical insights into the relationship between heuristic-driven biases and entrepreneurial strategic decision-making. The results suggest that heuristic-driven biases (anchoring and adjustment, representativeness, availability and overconfidence) have a markedly negative influence on the strategic decisions made by entrepreneurs in emerging markets. It means that heuristic-driven biases can impair the quality of the entrepreneurial strategic decision-making process.Practical implicationsThe article encourages entrepreneurs to avoid relying on cognitive heuristics or their feelings when making strategic decisions. It provides awareness and understanding of heuristic-driven biases in entrepreneurial strategic decisions, which could be very useful for business actors such as entrepreneurs, managers and entire organizations. Understanding regarding the role of heuristic-driven biases in entrepreneurial strategic decisions may help entrepreneurs to improve the quality of their decision-making. They can improve the quality of their decision-making by recognizing their behavioral biases and errors of judgment, to which we are all prone, resulting in a more appropriate selection of entrepreneurial opportunities.Originality/valueThe current study is the first to focus on links between heuristic-driven bias and the entrepreneurial strategic decision-making in Pakistan—an emerging economy. This article enhanced the understanding of the role that heuristic-driven bias plays in the entrepreneurial strategic decisions and more importantly, it went some way toward enhancing understanding of behavioral aspects and their influence on entrepreneurial strategic decision-making in an emerging market. It also adds to the literature in the area of entrepreneurial management specifically the role of heuristics in entrepreneurial strategic decision-making; this field is in its initial stage, even in developed countries, while, in developing countries, little work has been done.


2018 ◽  
Vol 41 (1) ◽  
pp. 2-28 ◽  
Author(s):  
Satyanarayana Parayitam ◽  
Chris Papenhausen

Purpose This paper aims to investigate the effect of cooperative conflict management on agreement-seeking behavior, agreement-seeking behavior on decision outcomes, moderating role of competence-based trust on the relationship between agreement-seeking behavior and decision outcomes, and mediating role of agreement-seeking behavior between cooperative conflict management and decision outcomes. Design/methodology/approach Using a structured survey instrument, this paper gathered data from 348 students enrolled in a strategic management capstone course that features strategic decision-making in a simulated business strategy game. The data from 94 teams were collected from the student population using a carefully administered instrument. The data were aggregated after running the inter-rater agreement test and the analyzed to test the hypotheses. Findings The results from the hierarchical regression of the complex moderated mediation model reveal that cooperative conflict management is positively related to agreement-seeking behavior, and agreement-seeking behavior mediates the relationship between cooperative conflict management and decision outcomes. The results also suggest that competence-based trust acts as a moderator in the relationship between agreement-seeking behavior and decision quality; agreement-seeking behavior and team effectiveness, and agreement-seeking behavior and decision commitment. Results also support mediation of agreement-seeking behavior between cooperative conflict management and decision outcomes. Research limitations/implications The present research is based on self-report measures, and hence, the limitations of social desirability bias and common method bias are inherent. However, adequate care is taken to minimize these limitations. The research has implications for the strategic decision-making process literature. Practical implications In addition to the strategic management literature, this study contributes to practicing managers. The study suggests that competence-based trust plays a vital role in decision effectiveness. Administrators need to select the members in the decision-making process who have competence-based trust on one another and engage in agreement-seeking behavior. Social implications The findings from the study help in creating a fruitful social environment in organizations. Originality/value This study provides new insights about the previously unknown effects of cooperative conflict management and agreement-seeking behavior in strategic decision-making process.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Fariborz Rahimnia ◽  
Homa Molavi

PurposeIn recent years, rapid changes in the economic situation and high levels of competition have increased the need for innovation in order to gain success. In such circumstances, organizational strategists are considered as critical in determining the success or failure of organizations. Using innovation in various aspects of organizational operations is the most important factor to achieve sustainable competitive advantages in industry. As a result, analyzing the effective factors involved in promoting the efficiency of innovative activities in the organization and ways of achieving it are of utmost importance. Thus, this paper examines the relationship between communication and innovation performance with respect to the intermediary role of strategic decision-making process speed.Design/methodology/approachThe present study has used quantitative methodology and questionnaire to collect data from 450 managers and members who are involved in the decision-making process in 150 companies operating in the food-industry sector. Data analysis was done by using structural equation modeling and AMOS software.FindingsThe results of the data analysis suggest that communication and strategic decision-making speed possess a significant positive impact on innovation performance. Also, strategic decision-making speed has sufficiently played the intermediary role between communication and innovation performance.Originality/valueThis survey specifies the effects of communication on the success of making fast strategic decision and innovation performance which aid Iranian food companies to tackle one of the managerial challenges: postponing strategic decisions due to lack of efficient communication to get information. In addition, to the best of the authors' knowledge, this essay is a first in Iran.


Author(s):  
Syahrizal Dwi Putra ◽  
M Bahrul Ulum ◽  
Diah Aryani

An expert system which is part of artificial intelligence is a computer system that is able to imitate the reasoning of an expert with certain expertise. An expert system in the form of software can replace the role of an expert (human) in the decision-making process based on the symptoms given to a certain level of certainty. This study raises the problem that many women experience, namely not understanding that they have uterine myomas. Many women do not understand and are not aware that there are already symptoms that are felt and these symptoms are symptoms of the presence of uterine myomas in their bodies. Therefore, it is necessary for women to be able to diagnose independently so that they can take treatment as quickly as possible. In this study, the expert will first provide the expert CF values. Then the user / respondent gives an assessment of his condition with the CF User values. In the end, the values obtained from these two factors will be processed using the certainty factor formula. Users must provide answers to all questions given by the system in accordance with their current conditions. After all the conditions asked are answered, the system will display the results to identify that the user is suffering from uterine myoma disease or not. The Expert System with the certainty factor method was tested with a patient who entered the symptoms experienced and got the percentage of confidence in uterine myomas/fibroids of 98.70%. These results indicate that an expert system with the certainty factor method can be used to assist in diagnosing uterine myomas as early as possible.


Author(s):  
Ekaterina Jussupow ◽  
Kai Spohrer ◽  
Armin Heinzl ◽  
Joshua Gawlitza

Systems based on artificial intelligence (AI) increasingly support physicians in diagnostic decisions, but they are not without errors and biases. Failure to detect those may result in wrong diagnoses and medical errors. Compared with rule-based systems, however, these systems are less transparent and their errors less predictable. Thus, it is difficult, yet critical, for physicians to carefully evaluate AI advice. This study uncovers the cognitive challenges that medical decision makers face when they receive potentially incorrect advice from AI-based diagnosis systems and must decide whether to follow or reject it. In experiments with 68 novice and 12 experienced physicians, novice physicians with and without clinical experience as well as experienced radiologists made more inaccurate diagnosis decisions when provided with incorrect AI advice than without advice at all. We elicit five decision-making patterns and show that wrong diagnostic decisions often result from shortcomings in utilizing metacognitions related to decision makers’ own reasoning (self-monitoring) and metacognitions related to the AI-based system (system monitoring). As a result, physicians fall for decisions based on beliefs rather than actual data or engage in unsuitably superficial evaluation of the AI advice. Our study has implications for the training of physicians and spotlights the crucial role of human actors in compensating for AI errors.


2021 ◽  
pp. 147612702110468
Author(s):  
James D Westphal ◽  
David H Zhu ◽  
Rajyalakshmi Kunapuli

We examine the symbolic management of participative strategic decision-making programs that purportedly use crowdsourcing technology to solicit strategic input below the executive suite, but are often decoupled from actual strategic decision making. Specifically, top management may decide on a strategic option before soliciting input under the program. The first portion of our theoretical framework explains why disclosure of a participative strategic decision making program in communicating with security analysts is associated with more positive analyst appraisals, despite decoupling, and why the benefits of disclosure are amplified to the extent that leaders highlight the use of crowdsourcing technology in the program. The second portion of our framework addresses the antecedents of symbolic adoption. We suggest that firms are more likely to adopt and decouple a program when the CEO has a personal friendship tie to the CEO of another firm that has adopted and decoupled, especially following relatively negative analyst appraisals. Analysis of a unique dataset that includes longitudinal survey data from executives supported our predictions.


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