Strategic Change Valuation

Section Three - Case Studies

Purpose: The purpose of the study was to examine the influence of strategic change on organizational growth at Beta Healthcare International Limited in Kenya. Methodology: The study was anchored on Agency Theory, Stewardship Theory, and Stakeholder theory to explain leadership accountability, managerial behavior, and stakeholder engagement during strategic transformation. An exploratory research design using a qualitative approach was adopted. Data was collected through in-depth interviews with seven purposively selected employees drawn from different functional areas of Beta Healthcare International Limited. The data were analyzed using thematic analysis with the support of NVivo software to identify patterns and themes related to digitization, organizational restructuring, communication processes, and training initiatives. Findings: The findings revealed that strategic change initiatives, particularly digitization and organizational restructuring, positively influenced operational efficiency, decision-making processes, and overall strategic alignment within the organization. However, the implementation of these initiatives faced several challenges, including inadequate internal communication, employee resistance to change, and unequal access to training opportunities. The results further demonstrated that effective training and capacity building initiatives significantly enhance employee adaptability and successful implementation of strategic change. Contribution to Theory, Policy and Practice: The study contributes to theory by demonstrating the continued relevance of Agency, Stewardship and Stakeholder perspectives in understanding the dynamics of strategic change implementation. Practically, the findings highlight the need for organizations to integrate digital transformation, structural alignment and human capital development to achieve sustainable growth. The study recommends strengthening internal communication systems, implementing inclusive and continuous employee training programs and adopting structured change management practices to enhance employee participation and reduce resistance to change. These measures are critical for improving organizational agility, competitiveness and long-term performance in healthcare sector.

Accurately inferring realistic subsurface structures according to different types of geophysical observations and interpretations remains a significant challenge as the morphology controls the subsurface flow and transport behavior. Hard data and soft data are most commonly used in subsurface characterization. Among them, hard data are observations obtained from subsurface measurements. Soft data are remotely sensed geophysical information and interpretations. The deep learning technique is able to automatically learn the nonlinear relationships and extract implicit features of prior samples. In this work, we propose a deep-learning-based multiple-condition fusion network (MCF-Net) to accurately characterize subsurface structures according to both hard and soft data. Two encoders are used to extract the deep implicit features of the hard and soft data in multiple-level representations. To effectively integrate the multiple-level representations of multiple data, multiple-condition fusion blocks are introduced to extract the representing characteristics. These blocks are also equipped for the reconstruction of heterogeneous structures. MCF-Net can accurately estimate subsurface structures using a variety of available observations. Experimental results prove the utility of MCF-Net in many fields of Earth science.

Categorization is known to play an important role in organizations because categories ‘frame’ situations in particular ways, informing managerial sensemaking and enabling managerial intervention. In this article, we advance existing work by examining the role of categorization practices in discursive leadership during periods of strategic change. Drawing on data from an ethnographic action research study of a strategic change initiative in a multi-national corporation, we use membership categorization analysis to develop a framework for studying ‘category predicates’ − defined as the stock of organizational knowledge and associated reasoning procedures concerning the kinds of activities, attributes, rights, responsibilities, expectations, and so on, that are ‘tied’ or ‘bound’ to organizational categories. Our analysis shows that discursive leadership enabled a radical shift in sensemaking about organizational structure categories through a process of ‘frame-breaking’ and ‘re-framing’. In so doing, the leader co-constructed a ‘definition of the situation’ that built a compelling vision and concrete plan for strategic change. We go on to trace the organizational consequences and material outcomes of this shift in sensemaking for the company in question. We conclude by arguing that ‘category predication work’ comprises a key leadership competence and plays an important role in organizational and strategic change processes.

In dynamic and uncertain business environments, marketing organizations need to be constantly ready to enact strategic changes. However, a robust measure for capturing the organizational capabilities and underlying marketing activities required to achieve effective marketing-related strategic changes is lacking. This study addresses this gap by developing a measurement tool for strategic change capability (SCC). Drawing on interviews with marketing consultants and senior marketing managers, the authors conceptualize SCC as a multidimensional dynamic marketing capability that comprises five dimensions: establishing the business case for change, preparing employees for change, setting up the organization for implementing change, institutionalizing change, and assessing and adjusting implementation. Following rigorous scale development procedures—including (1) item generation, (2) expert evaluation, (3) scale purification, (4) scale validity, (5) nomological and predictive validity, and (6) scale generalizability studies—a psychometrically sound and reliable measure of SCC is developed. The SCC scale facilitates different types of strategic marketing change and predicts performance outcomes better than established constructs (i.e., strategic flexibility, agility, adaptiveness, and responsiveness). This study contributes to the dynamic capabilities theory and provides empirically substantiated guidance for marketing organizations on how to prepare for and effectively enact strategic changes in dynamic business environments.

PurposeThis study aims to examine how senior foreign executives in a top management team catalyse strategic change in firms that originated from emerging markets (EMs). It further examines the moderating effects of organisational size and uncertainty avoidance (UA) on the positive relationship between senior foreign manager and strategic change in an organisation.Design/methodology/approachThe panel data econometrics and multilevel analyses were adopted to run the model. The author tests hypotheses on 263 emerging market firms (EMFs), originating from nine EMs.FindingsEmpirical results reveal that senior foreign managers are active agents who can promote and implement strategic change in an organisation. They possess a different set of values, knowledge and experiences that can trigger strategic change. In addition, firm size and UA weaken the relationship between senior foreign manager ratio and strategic change of a firm..Practical implicationsThis study indicates that recruiting committees of EMFs should consider hiring senior foreign managers to foster a higher degree of strategic change. Nevertheless, firm size and UA may impose implementation difficulties for senior, foreign managers. As a result, the focal firm should be flexible and open to change.Originality/valueThis study aims to contribute to strategic change and top management team internationalisation literature by promoting the role of senior foreign managers and national culture on strategic change.

The development of data fusion systems capable of incorporating soft human-generated data into the fusion process is an emerging trend in the fusion community, motivated mainly by asymmetric warfare situations where the observational opportunities for traditional hard sensors are restricted. This paper describes an extension of our prototype soft/hard data fusion system, based on the random set theory, from centralized into a fully distributed computational framework. A fully distributed data fusion algorithm relies only on information exchange between local sensor nodes and hence promises enhanced scalability, reliability, and robustness in contrast to the conventional centralized fusion approach. We propose a novel approach for distributed estimation of average soft data using the consensus propagation algorithm. The distributed estimation of aggregated hard data is accomplished through an average consensus filter. Based on the proposed approach, we describe a single-target tracking system capable of processing soft and hard data. The preliminary experiments demonstrate the efficiency of the consensus propagation based approach for distributed aggregation of soft data, as well as the advantages of incorporating soft data into the distributed data fusion process.

ABSTRACTThis study describes the strategic change efforts of a university in the United Kingdom which changed its form and resource deployments to focus on the production of interdisciplinary research. A problem-oriented case study method was used to chronicle and analyse the leadership strategies and tactics employed and their consequences. We found that the reliance on a vertical leadership (controlling) strategy led to external legitimization but not internal legitimacy. We also found instances these strategies created unintended consequences which inhibited the strategic change initiative. In particular, horizontal leadership (enabling) strategies that spoke to the academic heartland were muted. We concluded that in universities undertaking major strategic change efforts controlling influence actions may be necessary but they are insufficient to levers of strategic change. The study is particularly important because it contributes to an understanding of strategic change in universities at a time when most such efforts fail to meet their objectives and there is a limited empirical literature to draw upon.

A geostatistical methodology is proposed for integrating elevation estimates derived from digital elevation models (DEMs) and elevation measurements of higher accuracy, e.g., elevation spot heights. The sparse elevation measurements (hard data) and the abundant DEM-reported elevations (soft data) are employed for modeling the unknown higher accuracy (reference) elevation surface in a way that properly reflects the relative reliability of the two sources of information. Stochastic conditional simulation is performed for generating alternative, equiprobable images (numerical models) of the unknown reference elevation surface using both hard and soft data. These numerical models reproduce the hard elevation data at their measurement locations, and a set of auto and crosscovariance models quantifying spatial correlation between data of the two sources of information at various spatial scales. From this set of alternative representations of the reference elevation, the probability that the unknown reference value is greater than that reported at each node in the DEM is determined. Joint uncertainty associated with spatial features observed in the DEM, e.g. the probability for an entire ridge existing, is also modeled from this set of alternative images. A case study illustrating the proposed conflation procedure is presented for a portion of a USGS one-degree DEM. It is suggested that maps of local probabilities for over or underestimation of the unknown reference elevation values from those reported in the DEM, and joint probability values attached to different spatial features, be provided to DEM users in addition to traditionally reported summary statistics used to quantify DEM accuracy. Such a metadata element would be a valuable tool for subsequent decision-making processes that are based on the DEM elevation surface, or for targeting areas where more accurate elevation measurements are required.

The advent of County Governments in 2013 made many Kenyans optimistic that these devolved governments would deliver on public services more effectively compared to its predecessor. Nevertheless, the execution of various county plans, including the County Integrated Development Plans (CIDP), has not achieved the anticipated outcomes in numerous counties. Data from the Kenyan Institute for Public Policy Research and Analysis (KIPPRA) reveals that merely 30% of change initiatives within Kenyan county governments are fully implemented. Strategic leadership and stakeholder engagement has been touted as a possible remedy to such scenarios. This study explored the relationship between strategic leadership and change management in Bungoma County's local governance, specifically investigating how stakeholder engagement moderates this relationship. Anchored on strategic leadership theory, the study conducted a census of 73 respondents, adhering to a positivist paradigm and utilizing a causal research design. Data was collected using questionnaires. A pilot was conducted in Kakamega County to ensure data quality. Quantitative data was analyzed using SPSS version 26 for inferential statistics. The findings revealed that strategic leadership has significant statistical effect on change management. Stakeholder engagement was found to have significant moderating influence on the relationship between strategic leadership and change management. The study concluded that stakeholder engagement significantly moderated the relationship between strategic leadership and change management in County Governments of Bungoma, Kenya. To improve management outcomes, it is recommended that the County Government of Bungoma focus on strengthening its strategic leadership practices, particularly in the areas of strategic planning, corporate culture and organizational control. This could be achieved through targeted leadership development programs that equip managers with the necessary skills to effectively lead change initiatives.

Facilitating and inhibiting factors behind strategic change: Evidence in the Spanish private banking industry, 1983–1997

Restructuring the UK defence industry: Market pressures and management initiatives

In this study we demonstrate a methodology to combine two types of data -soft and hard data to predict facies in one of the fields of the Gulf of Mexico. We start with the formulation of the problem of data scarcity, underrepresentation and/or overrepresentation of facies or absence of well data (hard data) altogether. These issues addressed by rigorous physics-based modeling and generation of the soft data via Rock Physics Modeling. Soft data is then used as a training domain for facies classification within the field. The workflow is extended to use both hard- and soft-data obtained from well logs and Rock Physics Modeling to classify facies in a more geologically plausible manner compared to the scenario in which equiprobable prior distributions are assumed. This approach honors the knowledge of local geology and results in a more realistic classification of the facies.KeywordsRock physicsReservoir characterizationFacies predictionSoft dataHard data

Participation in strategic change processes is frequently assumed to have a number of positive consequences for decision quality, affective responses to change and success of strategic change implementation. To date little research has successfully established the validity of these claims. The fact that results from research into the effects of participation in other contexts are inconclusive is adding to the ambiguity concerning participation's efficacy in a strategic change context. This article uses data from a major strategic reorientation of a national telecommunications firm in order to assess the outcomes of participation in strategic change. Findings indicate a strong positive relationship between participation and goal achievement and organizational commitment, and a strong negative relationship with resistance. The results also suggest that the effects of participation are moderated by the changes' compatibility with organizational culture and the personal goals of change recipients.

New energy enterprises are important production and operation units engaged in the nature of new energy in the national economy. With the development of modern society, it is crucial to have a deep understanding of new energy enterprises, especially in the face of changing environment, and how to carry out strategic transformation of new energy enterprises. In a constantly changing environment, strategic change is a key issue and a central issue in the field of management and strategy. Time is the foundation of all research on strategic change, whether or not it is recognized by existing research. In this paper, the factors that influence strategic change in new energy companies are critically reviewed from a temporal perspective. Firstly, the development status of new energy enterprises is analyzed, the strategic change is defined, and then the influencing factors are obtained by integrating the relevant studies of the time dimension in the change activities. Based on the time perspective, the dynamic understanding of the strategic change process of new energy enterprises can be improved.