Technology adoption is a concern of business practitioners, policy makers and academics. Slow or low adoption can deprive stakeholders from intended benefits. Existing theories concerning technology adoption mostly focus on factors within a single organization. In this concept paper, we argue that sequential coherence which addresses knowledge flows that cross borders between organizations can provide enhanced insights in understanding technology adoption. Sequential coherence takes into consideration factors of both the transferor organization and the recipient organization. We propose a novel conceptual model of technology adoption based on sequential coherence. It takes into consideration the perceived usefulness and perceived ease of using technology. We have coined the model CUE (Coherence, Usefulness and Ease of use) of technology adoption. The CUE model can be used by practitioners, policy makers and academics.
Despite its popularity as a strategy to accelerate innovations there is evidence that open innovation does not always increase innovation performance. Extant literature provides inconsistent and inconclusive arguments in respect of the relationship between open innovation practices and innovation performance. Existing theories mostly have an internal focus and fall short of explaining why some firms succeed in open innovation initiatives and why others fail. Open innovation is about knowledge flows. We argue that boundary conditions matter in innovation performance and sequential coherence can explain why some succeed while others fail in open innovation. A qualitative inquiry we made reveals that sequential coherence that facilitates the knowledge transfer at boundary level influences innovation performance in open innovation initiatives. Sequential coherence is measured through the push and the pull effects by willingness and ability of the participants of teacher firm and the preparedness and ability of the participants from the student firm respectively. We trust that our findings bridge a gap in open innovation literature. These initial findings could be generalized through a quantitative study with larger samples. Managerial implications of the finding is that ability to scan the entire chain of knowledge flow across boundaries and taking corrective measures for any bottlenecks or hindrances observed can bring better results from open innovation initiatives. Further, sequential coherence leads to multiple research opportunities in furthering our knowledge in open innovation.
The prime objective of the research was to determine how the apparel manufacturing sector is embracing digitization and its leaders are preparing for the digital age? so we wanted to find out what type of leadership style is needed for digital leadership. The present study used a sample of 50 RMG companies. We investigated relationships between three variables, Internet od Things, use of digitization-automation, use of smart phones and apps. Further, the variables’ influence on digitization has been assessed through multiple factors leading to digitization by allotment of weightage for each factor. The findings in this paper supports two variables; use of automized digital machines and internet of things being significant whereas, use of smartphones and apps is insignificant. It implies that preparation for leading in the digital age remains limited which require change oriented leadership behavior at all levels. Limitations of the paper include the data which is specific to Bangladesh RMG industry, therefore it cannot be generalized, further the economic meltdown due to COVID-19 pandemic might have influenced the results. The paper’s prime contribution is based on the assessment of predictor variables and their influence that it makes in providing leadership in the digital age which demand change oriented behavior of leaders.
Open innovation, which encourages firms to use external knowledge and external partners to accelerate innovation, has become a popular approach among organisations globally. Researchers have highlighted multiple benefits that open innovation offers. Extant literature often discusses factors of open innovation that increase innovation performance. However, open innovation does not always bring higher innovation performance and reasons for this are not adequately addressed in the existing literature. The objective of this research study is to increase understanding of factors that can hinder innovation performance in open innovation implementations. Special attention has given to convergence. In this case, convergence refers to alignment and coordination between innovation partner firms. The empirical data for this research study will be gathered from software firms in Sri Lanka. The background for this study is the software firms in Sri Lanka which have not reached the expectation that have been placed on them.
The aim of this paper is to introduce two novel variables that can explain variations of innovation performance in open innovation initiatives. Open innovation is a popular strategy among business organizations in promoting innovations. However, it does not always increase innovation performance. The reasons for the varying innovation performance in open innovation initiatives cannot be fully explained by the existing theories and variables used. This article explains how a mixed method research that has been undertaken with the objective of identifying novel determinants to explain varying innovation performance in open innovation initiatives has been progressing up to its final phase. This research follows a sequential exploration strategy as its research design. The ontology of the subject research is pragmatism. Two new determinants identified through the qualitative inquiries namely time orientation and
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