Purpose The purpose of this study is to contribute to the current discussion on strategic alignment of information technology and business (strategic alignment) by developing a model for conceptualizing how strategic alignment can be enabled through of IT flexibility and IT capability. Design/methodology/approach A questionnaire instrument was created to measure the constructs and it was assessed in a pretest and two pilot-tests. The main data set was collected from IT managers (or similar titles) of medium- and large-sized firms. Findings Strategic alignment seems to be moving closer to firms’ core activity in today’s business environment. The findings revealed that strategic alignment was significantly affected by four dimensions of IT flexibility and IT capability. Furthermore, the significant role of two dimensions of IT flexibility in IT capability was supported. Research limitations/implications Single key informants were used for data collection that could be a potential limitation. Practical implications It seems likely that firms will benefit from the results to manage and control their scarce IT resources more effectively for aligning IT with business strategies, goals and needs. Originality/value Strategic alignment has become a more complex and unstructured phenomenon and many firms are still considering how to reconcile to it. Furthermore, the lack of empirical examination of IT flexibility and IT capability in relation to strategic alignment from important perspectives, and the lack of research of the dimensions of IT flexibility for supporting IT capability, determines the purpose of this study.
What seems to still be the main concern for managers in the corporate world across the globe is ITbusiness strategic alignment. This study seeks to address the research problem about the lack of alignment between IT and business strategies. Upon reviewing various literature on this subject, it was found that IT flexibility is one of the most vital factors that help sustain strategic alignment. The researcher upon having a detailed discussion on the possible areas associated with the present body of knowledge has discovered gaps in the studies that have been undertaken on strategic alignment and IT flexibility. This is because IT capability in relation to IT flexibility and strategic alignment has been ignored in the previous studies. As a result, this research proposes a relationship between IT flexibility (i.e., modularity, connectivity and compatibility), IT capability, and strategic alignment.Many studies have suggested the importance of strategic alignment which is due to several reasons. Firstly, strategic alignment is effective in ensuring that areas which are critical for successful business performance are targeted by information systems (IS) [18]. Secondly, it is valuable in enhancing the understanding of top executives about the importance of IS, and simultaneously, improving the understanding of IS managers with regard to business goals [19]. Apart from that, strategic alignment is also successful in ensuring Information Strategic Planning (ISP) is in conjunction with Business Planning (BP) activities in order for IS operations to back business strategies better and participate in business value accomplishment [20]. In another study [21], strategic alignment can successfully speed up acquirement and strategic placement of IT that is in harmony with the competitive needs of the establishment as opposed to the current practice trends in the establishment. Definitions of Strategic AlignmentA variety of conceptualizations and explanations are applied in the literature to explain strategic alignment. These are discussed below:The extent to which the information technology mission, objectives, and plans support and are supported by the business mission, objectives, and plans [22], [23]. The fit between IT and business structures is defined by Jarvenpaa and Ives [24]. The association among IS strategic orientation and business strategic orientation in IS strategic alignment is explained [25]. Applying IT in an appropriate and timely way, in harmony with business strategies, goals and needs [26], [27]. The positioning of four parts, which are business strategy, IT strategy, organizational infrastructure and processes and IS infrastructure and processes in strategic alignment is stated [27]. over 7 years of University teaching experience.
Strategic alignment or the fit between information technology (IT) and business strategy remains a key topic of concern among managers worldwide. Change has always being considered the foremost challenge affecting strategic alignment. Planning for alignment in uncertain and dynamic environments is fraught with risk as organizations seek to understand how much flexibility to add to their IT infrastructure so as to maintain consistently high levels of alignment. Reviewing the literature showed that there is a positive relationship between IT infrastructure flexibility and strategic alignment with strategic information systems planning (SISP) serving as a moderator of this relationship. Additionally, according to literature on exporting area and logical arguments we proposed that export performance can moderators the link between IT flexibility and strategic alignment. Also, studies results emphasize the need for organizations to use SISP to consistently monitor the relationship between IT flexibility and alignment. Doing so during periods of increased change in dynamic and uncertain environments reduces the risk of being ensnared by rigidity traps that could transform IT into an inhibitor rather than an enabler of change.
Social networks attract much attention due to their ability to replicate social interactions at scale. Link prediction, or the assessment of which unconnected nodes are likely to connect in the future, is an interesting but non-trivial research area. Three approaches exist to deal with the link-prediction problem: featurebased models, Bayesian probabilistic models, and probabilistic relational models. In feature-based methods, graphical features are extracted and used for classification. Usually, these features are subdivided into three feature groups based on their formula. Some formulas are extracted based on neighborhood graph traverse. Accordingly, there exist three groups of features: neighborhood features, pathbased features, and node-based features. In this paper, we attempt to validate the underlying structure of topological features used in feature-based link prediction. The results of our analysis indicate differing results from the prevailing grouping of these features, which indicates that current literatures' classification of feature groups should be redefined. Thus, the contribution of this work is exploring the factor loading of graphical features in link prediction in social networks. To the best of our knowledge, no prior studies had addressed it.
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