Collaboration formation has been on the increase among software development firms due to rapid advancement in technology, requirements for diverse skills, and fierce competition. By collaborating with a suitable partner, a firm can benefit from its diversified skills, utilize its experience, share costs, and reduce the product completion span. As a result, a better quality product that offers more profits can be developed. However, forming an alliance with an inappropriate partner or an unfair profit and cost distribution mechanism may result in failure. The existing mechanisms offer poor results either due to inappropriate partner selection criteria or due to unfair profit distribution because of the bargaining power advantage to one of the negotiating firms. To address the aforementioned issues in the criteria for partner selection and profit sharing, this paper formulates the strategic interaction between firms for the partner selection and profit sharing as a Shapley value-based cooperative game theoretic model. Our model enables a firm to not only select a suitable partner but also offer a fair profit distribution mechanism. Our cooperative game model takes into account the knowledge investment, stock of knowledge, knowledge absorption capacity, coordination cost, and development cost of firms. The model is analyzed with various scenarios under which collaboration formation occurs and provides different strategies regarding collaboration such as not collaboration (NC) and collaboration (C). The proposed model provides a better joint payoff as well as a higher and fair share of the joint profit for each firm.
Fog Computing (FC) was introduced to offer resources closer to the users. Researchers propose different solutions to make FC mature and use simulators for evaluating their solutions at early stages. In this paper, we compare different FC simulators based on their technical and non-technical characteristics. In addition, a practical comparison is conducted to compare the three main FC simulators based on their performance such as execution time, CPU, and memory usage for running different applications. The analysis can be helpful for researchers to select the appropriate simulator and platform to evaluate their solutions on different use cases. Furthermore, open issues and challenges for FC simulators are discussed that require attention and need to be addressed in the future.
Requirement for formation of collaborations has been on increase for the software development industry, especially for smaller to medium sized firms, due to rapid technological advancements, requirements for diversified skills, ever enhancing demands for innovation and fierce competition. Collaborative product development in an alliance enables the firms to benefit from each other’s diversified skills and the experience as a result of which they can develop products more rapidly and of better quality as well resulting in a higher payoff. Also, the development costs decrease. However, to avoid undesired results, selection of an appropriate partner firm for collaboration is of utmost importance keeping in view the objectives of alliance formation of both the strategic partners. One-way partner selection techniques available in the literature are impractical as they enable a firm to rank potential partners only from its own perspective while ignoring their objectives. This problem is addressed by the two-way partner selection techniques, however, they either ignore the payoff distribution criteria or the proposed criteria is unfair. More importantly, existing techniques consider that firm collaborate only with the objective to enhance their financial payoff which might not always be the case. The fact that collaborating firms may have one but different objectives for collaboration, or, each may have multiple objectives is largely neglected. To address the scenarios in which firms may collaborate due to multiple and possibly different objectives, this work proposes a bi-objective game-theoretic model that enables a firm to select an appropriate partner based on the individual preferences of both on the following two objectives: 1) learning and 2) financial revenue. Moreover, this model calculates the pay-off that each firm should get whether only monetary, only in the form of learning or both. The calculation of payoff share is based on the following parameters: 1) individual goals of collaboration of partner selecting firms on the said two objectives, 2) their level of cost contribution, 3) cooperation ratio and 4) knowledge investment difference. Comprehensive analysis of various scenarios is done for the proposed Nash Bargaining payoff distribution model to find the optimum strategy of collaborating firms for each scenario.
No abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.