infonet-economy

The purpose of this research was to explore self-directed learning (SDL) in the context of online learning. The experiences of traditional and nontraditional learners engaged in an online course as part of a degree-seeking program are explored in terms of readiness for SDL and the processes of planning, monitoring, and evaluating one’s own learning in the online context. The findings present small nuances in how different learners describe SDL in the online context related to how the different students perceive their learning in an online course. Traditional learners discuss the impact of the flexible nature of online learning as it relates to the process of SDL while nontraditional learners focus more on the learning process itself. Areas for future study in the area of SDL in online learning are shared to highlight the importance of exploring adult learning theory in the online context from both learner and educator perspectives.

This paper applies a social capital perspective to study how business units leverage individuals’ external networks to explore and exploit resources outside the firm’s boundaries. We explore this matter inductively by analysing the development and leveraging of social capital at the business unit level in a global commodity company. Our findings show how individuals’ strong and weak network ties support business unit ambidexterity. We also explore the characteristics of the supportive organisational context that allows firms to reap the benefits of their employees’ external social relationships. This study deepens our understanding of exploration and exploitation at both the individual and business unit levels and contributes to research on contextual ambidexterity.

Our study examines the nomological network of active procrastination in comparison with passive procrastination. In particular, we examine the effects of the five factor model with the aim to understand which personality traits predict academic procrastination. We also test the effect of passive and active procrastination on academic performance to study the unique contribution of each type of procrastination. In a sample of 178 university students in Switzerland, we find that extraversion and neuroticism are related to active procrastination. Furthermore, active procrastination predicts GPA to a much greater extent than the five factor model and passive procrastination.

Given the importance of personality to predict consequential outcomes in the workplace, it is important to be able to measure it accurately. To date, no research has examined if people leave valid cues of their personality in résumé photographs. This research examined to what extent résumé photographs provide accurate information about the personality traits of their owner. Two observers rated 97 résumé photographs on four aspects: color photograph, photograph background, smile and professional attire. These ratings were compared with an accuracy criterion of the big five dimensions (self and peer reports). Results indicate that three out of the four cues are linked to extraversion, conscientiousness, agreeableness and emotional stability. These results suggest that résumé photographs can convey valid information about personality.

A principal-agent relationship exists between hotel owners and the management companies which often operate their hotels. In addition, they both act as principals to a mutual agent, the hotel's General Manager, who is tasked with trying to achieve each parties' objectives. Extensive research on hotel management agreements which govern the owner-operator relationship has demonstrated that these objectives are often incongruent. However, the property-level managerial and performance implications of their goal incongruence has not been empirically examined. This study analyzes these issues using a matched sample of surveys from both owners and operators across 64 hotels operated under hotel management agreements. Using structural equations modeling, we demonstrate that owner-operator goal congruence positively impacts hotel performance and that this relationship is both mediated and moderated by the hotel General Manager's autonomy.

Entrepreneurship and the startup phenomenon have received considerable attention from researchers, with a particular focus on topics such as the identification of: new ventures’ success factors, conditions that foster entrepreneurial processes and new venture creation (Grimaldi & Grandi, 2005; Maine et al., 2015; Roberts, 1991; Smilor, 1987; Sternberg, 2014; Stuart & Abetti, 1987; Timmons et al., 1999). Accelerators are part of a wide range of initiatives aimed at stimulating and supporting entrepreneurship (Pauwels et al., 2016). The acceleration concept aims to link innovative startups, access to capital and training in order to accelerate the growth of early-stage ventures, and thus speed up the transformation process from startup to a sustainable company. Accelerators assist ventures by providing mentorship and training to a specific cohort of startups through a structured and fixed-term program (Cohen & Hochberg, 2014). In addition, accelerators may offer financing (Christiansen, 2009; Miller & Bound, 2011). While accelerators do have certain common traits, they also differ widely depending on their funding sources, industry focus, start-ups base (customer), network, and resources. These differences give rise to different acceleration models. In this paper, we identify five (different) main types of accelerators: Independent Accelerators (IA), Corporate Accelerators (CA), Hybrid Accelerators (HA), University Accelerators (UA), and Government Accelerators (GA). We then describe their main features, similarities, and differences on the basis of what we define as the accelerators’ ‘characterizing’ variables (institutional mission/strategy, industry vertical, location, market orientation, origin of projects, stage, program duration, sources of revenue, support offered, management, network). We argue that the diversity of acceleration models has been driven by the innovative power of startups to develop new technologies, new business models, and foster the regional and economic development of the region in which they operate. By studying the dynamics of the accelerator industry, we identified two main acceleration models, Model 1 and Model 2, which provide accelerators with useful strategic indications on how and where to position themselves in an ecosystem. To exemplify our results, we report empirical evidence from case studies of eight Swiss accelerators. Going through the accelerators’ characterizing variables allowed us to capture the main differences between the five types of accelerators to support our two-accelerator-models (view). In our conclusions, we highlight the importance of a range of accelerators, offering various benefits to satisfy different startups. Accelerators need to understand their strategic positioning within their ecosystem, and realize how their focus matches the variety of demands and expectations coming from startup ventures.

While business model innovations are critical to a company’s long-term strategy, they are still poorly understood compared to other kinds of innovations. In this paper, we investigate prior research and reframe business model innovation through a top management lens. We report on a content analysis of interviews with top managers of small and medium enterprises in the technology industry, with the aim of recording their definition of business model innovation ans their impact on strategy. This research intends to contribute to a better understanding of the meaning of business model innovation from a practitioners’ perspective and its impact on strategy. These findings open new directions for theory development and empirical studies in the business model and strategic management literature.

Accelerators assist early-stage ventures by offering networking opportunities, access to funding and training. We map business accelerators in five categories: Independent Accelerators (IA), Corporate Accelerators (CA), Hybrid Accelerators (HA), University Accelerators (UA), and Government Accelerators (GA). We argue that accelerators can be described by two main acceleration models (Model 1 and Model 2), providing accelerators with valuable information on how to position themselves strategically in the ecosystem. We identify a list of accelerators’ ‘characterizing’ variables that allows for differentiating the five accelerator categories and describing the various acceleration models. Empirical evidence is provided on the two acceleration models based on a case study of eight Swiss acceleration programs.