Technologies, such as Chat Generative Pre-Trained Transformer (ChatGPT), are prime examples of Generative Artificial Intelligence (AI), which is a constantly evolving area. SMEs, particularly startups, can obtain a competitive edge, innovate their business models, gain business value, and undergo a digital transformation by implementing these technologies. Continuous but gradual experimentation with these technologies is the foundation for their adoption. The experience that comes from trying new technologies can help entrepreneurs adopt new technologies more strategically and experiment more with them. The urgent need for an in-depth investigation is highlighted by the paucity of previous research on ChatGPT uptake in the startup context, particularly from an entrepreneurial perspective. The objective of this research study is to empirically validate the Generative AI technology adoption model to establish the direction and strength of the correlations among the adoption factors from the perspectives of the entrepreneurs. The data are collected from 482 entrepreneurs who exhibit great diversity in their genders, the countries in which their startups are located, the industries their startups serve, their age, their educational levels, their work experience as entrepreneurs, and the length of time the startups have been on the market. Collected data are analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) technique, which results in a statistical examination of the relationships between the adoption model’s factors. The results indicate that social influence, domain experience, technology familiarity, system quality, training and support, interaction convenience, and anthropomorphism are the factors that impact the pre-perception and perception phase of adoption. These factors motivate entrepreneurs to experiment more with the technology, thereby building perceptions of its usefulness, perceived ease of use, and perceived enjoyment, three factors that in turn affect emotions toward the technology and, finally, switching intentions. Control variables like age, gender, and educational attainment have no appreciable effect on switching intentions to alternatives of the Generative AI technology. Rather, the experience factor of running businesses shows itself to be a crucial one. The results have practical implications for entrepreneurs and other innovation ecosystem actors, including, for instance, technology providers, libraries, and policymakers. This research study enriches the Generative AI technology acceptance theory and extends the existing literature by introducing new adoption variables and stages specific to entrepreneurship.

This paper presents a fuzzy inference method to investigate the impact of project-based assessment on the desirable outcomes by analyzing students creative and critical thinking, collaborative decision-making, and communication skills with realistic constraints and standards through theory and practical implementation in (a) course attainment and (b) on overall program attainment carried out in engineering discipline. This paper uses twelve specific parameters to capture program attainment parameters (PAPs). It proposes three main parameters to define various assessment system elements required for assessing course attainment parameters (CAPs), correlated with each other. To the best of the author's knowledge, to date, there is no defined mathematical tool to map CAPs to PAPs. Thus, this paper proposes assessment pedagogy to evaluate the PAPs corresponding to CAPs to handle the vague correlation mapping using fuzzy logic. The methodology and the preliminary results conducted for one year are promising, helping educators evaluate a candidate's performance individually or in a group on several assessment criteria, assisting in attaining the knowledge, values, attitude, deep learning, and skills needed for sustainable education development.

Startups have high failure rates due to their inability to attain a sufficient product/market fit, i.e., delivering a solution that best matches the user needs in the market. Requirement engineering is the activity that could help startup teams identify the value proposition that provides high value to the users and continuously innovate it. The objective of the study is to analyse the state of art of the requirement engineering research in the context of startups, as available in the literature. The analysis of the research area highlights the research trends to achieve two things i.e., (a) predict how much support the startups can get from the literature for enhancing their success rates and (b) identify the research gaps to motivate researchers to conduct future research that could be adoptable in startup contexts. Systematic mapping is conducted on studies extracted from the four bibliographic databases (IEEExplore, ACM, Springerlink and ScienceDirect) and studies extracted by using a forward snowballing approach. Individual studies are coded to yield the classification scheme. Formulated schemes and those already available in literature, were populated with information extracted from the abstracts of the studies. The research is mostly focused on generic requirement engineering and product validation activities. The research is conducted mostly as evaluations (empirical studies) with the outcome of providing theory to the research community. Major underlying motivation of the research is to attain the product/market fit. However, research studies focusing on requirement documentation, prioritization and elicitation are losing focus from 2017, 2018 and 2019, respectively. The literature lacks the studies that reports research solutions which are validated in laboratory settings or in real contexts, experience reports, opinion papers and philosophical papers. The positive side of the finding is that the number of requirement engineering research studies in a startup context have increased in the past five years. At this instant, unfortunately the literature has limited ability to support startups by providing solutions (for instance, research solutions, evidence to support decision makings, best practices, experiences etc.) that are adoptable in their real context. Uniform focus of the researchers across all sub-activities of requirement engineering is required with effort distributed across different research types that supports startups, not only by providing validated solutions but experience reports, opinions, new conceptual frameworks and empirical evidence that can aid their decision making.

[Context] The software startups could continuously innovate business model value proposition by involving freelancers as a source of innovative ideas (that enhance customer perceived value) and as experts for implementing the innovative ideas (by undertaking software engineering tasks). Startups employ one of three strategies for associating with freelancers i.e., task based (association ends with completion of the outsourced task), panel based (outsourcing task to a panel of freelancers associated with startup), or hybrid. Uncertainties, terminology issues, high technical debt, lack of documentation, lack of systematic decision making processes, lack of resources, lack of brand values, need for the continuous involvement of the freelancer to incorporate continuous validated learnings, merging freelancer perspectives, and deciding the level of their involvement in individual requirement engineering (or value proposition innovation) activities, are the main inhibitors for associations with freelancers. The availability of good freelancers and their long term and continuous commitments are necessary requirements for value proposition innovation. The theory about freelancer association with the software startups is extended by studying the real practices of startups, which successfully involved freelancers for value proposition innovation by capturing innovative ideas and acquiring the freelancer’s skills to implement those ideas. [Objectives] The objective of this paper is to explain the strategies adopted by the software startups to foster value proposition innovation by continuously involving the freelancers and the way they overcome the challenges arising because of the associations. The findings are driven by the study of real practices of startups that proved to be successful in the market by involving freelancers and continuous innovations leading to increased market shares. [Method] This paper performs empirical studies through case studies of three software startups located in Italy, France, and India, which are at the verge of being transforming into big companies, with large market share. The current practices highlighting the successful way of executing freelancing association strategies for value proposition innovation and the way to overcome the arising challenges are reported. The findings are also compared with those of two young startups based in Switzerland and India, to bring useful lessons for the young startups. The case study results are validated by employees from the studied startups (both those who participated in data collection and those who did not). [Results] The results indicate that freelancer involvement during value proposition activities, which is the core business operation, is beneficial to the both freelancers and the startups. Startup teams could reduce the development costs, shorten time to market, and increase customer satisfaction (by providing features addressing real market needs) by correctly involving the freelancers uniformly across value proposition activities. The startups could manage innovation with small teams (compared to human resources in companies) if done jointly with the freelancers, that helps the team members to learn new skills, upgrade their skills, and learn new perspectives about their markets. Business impacts due to freelancer involvement are stronger if the level of freelancer involvement across various value proposition activities is higher compared to their involvement across few activities only. The studied startups are not completely dependent on the freelancers but the freelancer’s perspectives and skills are valued as a rich source of market success. Freelancer involvement is taken as an opportunity to gain access to global market perspectives, which otherwise would be effortful for in-house teams to collect. In addition, they resolve technical debt, are a source of upgrading skills for undertaking future innovation, and help reaching customers for marketing (promoting product and gaining access to the feedbacks). Overall, the value proposition innovation in the studied startups have different levels of involvement of the freelancers but these startups have reported positive impacts on the business in terms of development cost reductions, shorten time to market, and high customer satisfaction (measured on early attainment of product/market fit and fast growth thereafter). The case study results are validated by the startup employees (member checking). The responses collected are analysed using box plots, which shows a higher level of result agreements among the employees.

Context: freelancers and startups could provide each other with promising opportunities that lead to mutual growth, by improving software development metrics, such as cost, time, and quality. Niche skills processed by freelancers could help startups reduce uncertainties associated with developments and markets, with the ability to quickly address market issues (and with higher quality). This requires the associations between freelancers and startup to be long-term, based on trust, and promising agreements driven by motivations (leading to the growth of both parties). Freelancers could help startups foster innovations and undertake software development tasks in better ways than conducted in-house, if they are selected using informed decision-making. Objectives: the paper has three objectives, (1) to explore the strategies of startups to outsource software development tasks to freelancers (termed as freelancing association strategies); (2) to identify challenges in such outsourcings; and (3) to identify the impacts of outsourcing tasks to freelancers on overall project metrics. The overall objective is to understand the strategies for involving freelancers in the software development process, throughout the startup lifecycle, and the associated challenges and the impacts that help to foster innovation (to maintain competitive advantages). Method: this paper performs empirical studies through case studies of three software startups located in Italy, France, and India, followed by a survey of 54 freelancers. The results are analyzed and compared in the identification of association models, issues, challenges, and reported results arising because of such associations. The case study results are validated using members checking with the research participants, which shows a higher level of result agreements. Results: the results indicate that the freelancer association strategy is task based, panel based, or a hybrid. The associations are constrained by issues such as deciding pricing, setting deadlines, difficulty in getting good freelancers, quality issues with software artefacts, and efforts to access freelancer work submissions for reward. The associations have a positive impact on software development if there is availability of good freelancers (which lasts long for various tasks). The paper finally provides a freelancing model framework and recommends activities that could result in making the situation beneficial to both parties, and streamline such associations. Fostering innovation in startups is, thus, a trade-off situation, which is limited and supported by many conflicting parameters.