View Of Execution Research Articles

The Effectiveness of Executive Coaching: Executive Views and Metrics

The Effectiveness of Executive Coaching: Executive Views and Metrics

PRODUCT QUALITY (PQ) IDENTIFICATION IN MANUFACTURING COMPANIES: THE PERSPECTIVE OF MANAGERS AND EXECUTIVES

Pursuing quality as one of the main goals of a competitive manufacturing company is very important. The quantity of features and characteristics of a product reflects its quality. One of the most important aspects is that managers and executors (team members) must understand the importance of quality and know what factors affect it and what solutions take place with identified problems. Based on the identification of product quality from the point of view of managers and executives, problems are identified, and solutions are provided to change the situation. If they do not have a common understanding of product quality issues, the situation in production only worsens. Decision-making often requires access to real-time data, analytics, and resources that are typically managed by relevant departments or MANAGERS. Expected, that EXECUTORS follow established procedures and report issues to their MANAGERS. Organizations must empower their frontline employees with the authority and training to make decisions related to equipment operation and maintenance. The results of the Exploratory research revealed that the work of managers and executives with product quality has a lot of disadvantages. The general perspective of managers and executors in solving product quality problems and making decisions to eliminate them include a shared understanding of quality standards, effective communication, data-driven decision-making, empowerment, a commitment to continuous improvement, problem-solving skills, resource allocation, risk management, ongoing training, customer focus, and documentation. Organizations must empower their frontline employees with the authority and training to make decisions related to equipment operation and maintenance. In such cases, EXECUTORS are expected to exercise their judgment and expertise to keep operations running smoothly. The general perspective of managers and executors in solving product quality problems and making decisions to eliminate them include a shared understanding of quality standards, effective communication, data-driven decision-making, empowerment, a commitment to continuous improvement, problem-solving skills, resource allocation, risk management, ongoing training, customer focus, and documentation. By working collaboratively and emphasizing these factors, organizations can effectively address and prevent quality issues.

An Examination of the Supply-Side Stakeholders’ Views towards Health Tourism Investments in the Region of Thessaly, Greece

The study aims to examine the views of local executives and managers in Thessaly, Greece related to the potential profitability of investing in the health tourism industry. Furthermore, the study attempts to shed some light on the factors that affect their views about health tourism investments. The data are collected through self-administered questionnaires to stakeholders in facilities that have the potential, or they are already, engaged in the health tourism industry. The sample is collected from a wide range of facilities, namely hotels, hospitals, private clinics, rehabilitation centres and nursing homes. Kendall’s tau-b correlation statistics and logistic regression models are employed to detect the driving forces on the formation of attitudes towards health tourism investments. Current research regarding health tourism in Greece is rather limited. In addition, the majority of relevant international studies examines factors shaping the demand side. The present study utilizes a sample from the supply side, thus of stakeholders in related sectors and can enhance our knowledge about their stances towards health tourism investments and the factors shaping these stances.

CLC: A cross-level program characterization method

Characterization of program execution plays a key role in performance improvement. There are numerous transformations applied to each step that a program takes on its lowering from source code to a compiler intermediate representation to machine language to microarchitecture-specific execution. The unpredictable benefit of each transformation step could lead a notionally superior algorithm to exhibit inferior performance once actually run, and it can be hard to discern which step in the transformation path contradicted the code developer’s assumptions.Conventional approaches to program-execution characterization consider the behavior after only a single one of those steps, which limits the information that can be provided to the user. To help address the issue of myopic views of program execution, this paper presents a novel cross-level characterization approach for understanding the behavior of program execution at different levels in the process of writing, compiling, and running a program. We show that this approach provides a richer view of the sources of performance gains and losses and helps identify program execution in a more accurate manner.

Robot learning from human demonstrations with inconsistent contexts

Visual imitation learning is a promising approach that promotes robots to learn skills from visual demonstrations. However, current visual imitation learning approaches introduce unreasonable assumptions that the contexts of the visual demonstrations and the robot observations are consistent, which affects the flexibility and scalability of the approaches. It is a key challenge for robots to learn from visual demonstrations with inconsistent contexts. Inconsistent contexts may cause a serious difference in the pixel distribution of the operator and the environment, which makes vision-based control policies hardly effective. In this paper, we propose a novel imitation learning framework to enable robots to reproduce behavior by watching human demonstrations with inconsistent contexts, such as different viewpoints, operators, backgrounds, object appearances and positions. Specifically, our framework consists of three networks: flow-based viewpoint transformation network (FVTrans), robot2human alignment network (RANet) and inverse dynamics network (IDNet). First, FVTrans transforms various third-person demonstrations into the fixed robot execution view. With a meta learning strategy, FVTrans can quickly adapt to novel contexts with few samples. Then, RANet aligns the human and the robot at the feature level. Therefore, the demonstration feature can be used as a subgoal of the current moment. Finally, IDNet predicts the joint angles of the robot. We collect a multi-context dataset on the real robot (UR5) for three tasks, including grasping cups, sweeping garbage and placing objects. We empirically demonstrate that our framework can perform three tasks with a high success rate and be effectively generalized to different contexts.

Dynamic and execution views to improve validation, testing, and optimization of autonomous driving software

Dynamic and execution views to improve validation, testing, and optimization of autonomous driving software

Fraud and Malfeasance: The Role of Cases When Teaching the Phenomenon in Accounting Education

The paper addresses a plea by accounting educators that ethics should be integrated into the accounting curriculum (Poje and Zaman Groff 2022). Further, accountants should teach ethics. Case learning is consistent with Bloom’s (1956) taxonomy of six levels of learning. The ethics literature supports using cases to teach ethics because cases allow each student to put themselves in the position of a decision-maker. Case selection should engage the learner emotionally. Therefore, current issues are preferable. With these goals—engaging the student as a learner, ensuring action learning, and meeting the learning taxonomy of Bloom, the paper provides educators with a suggested road map of case materials that can be employed in accounting courses across the program. Road maps are a means to demonstrate a holistic view of curriculum design and learning execution across specific accounting courses.

Using neural networks for sustainable construction business development

The authors look at the application of neural networks to sustainable business development in the construction industry. The actual work of self-learning neural networks with statistical data tables in construction is studied. The possibilities of managing construction scheduling and material supply requirements from the point of view of work execution with the participation of neural networks are shown. Appropriate statistical indicators can be used in subsequent numerical calculations. Tables above all allow for the systematisation of numerical information. The study of large number of tables by neural networks allows statistical study not only of the collective as a whole, i.e., of the totality of objects and phenomena - macro-units, but also of subdivided collectives, i.e., separate parts of the whole - micro units and complex units (united by one attribute). Therefore, the subject of statistical sentence-table may be statistical population as a whole (macro units), aggregate dissected (separate observation units) - micro units and separate aggregate - complex units. This is quite understandable, because statistical judgement can refer to the object of observation at any stage of this process, i.e. as a result of the dissection of the population into micro units, combination of the latter into small populations (complex units) and generalization of micro units and complex units into units of the concept - macro units.According to the results of implementation of the automated control systems based on neural networks the high purity and quality of design solutions based on the automated data processing of production and economic activity of the construction organisation is achieved. Their actual economic efficiency is calculated.

Application of expert systems as an element of sustainable development of educational process

The authors look at the application of neural networks to sustainable business development in the construction industry. The actual work of self-learning neural networks with statistical data tables in construction is studied. The possibilities of managing construction scheduling and material supply requirements from the point of view of work execution with the participation of neural networks are shown. Appropriate statistical indicators can be used in subsequent numerical calculations. Tables above all allow for the systematisation of numerical information. The study of large number of tables by neural networks allows statistical study not only of the collective as a whole, i.e. of the totality of objects and phenomena - macro-units, but also of subdivided collectives, i.e. separate parts of the whole - micro units and complex units (united by one attribute). Therefore the subject of statistical sentence-table may be statistical population as a whole (macro units), aggregate dissected (separate observation units) - micro units and separate aggregate - complex units. This is quite understandable, because statistical judgement can refer to the object of observation at any stage of this process, i.e. as a result of the dissection of the population into micro units, combination of the latter into small populations (complex units) and generalization of micro units and complex units into units of the concept - macro units.According to the results of implementation of the automated control systems based on neural networks the high purity and quality of design solutions based on the automated data processing of production and economic activity of the construction organisation is achieved. Their actual economic efficiency is calculated.

Chief Executive's View: Exciting times as we launch our new strategy 2023–2027

Chief Executive's View: Exciting times as we launch our new strategy 2023–2027

Reputation of Public Organizations: What Dimensions Are Crucial?

This paper explores the relationships among variables and determines the influences of dimensions (i.e., municipal satisfaction, organizational performance, perceived quality, contestations and complaints of the municipal executive) on the notoriety, image, and reputation (NIR) of municipal executives. We attempted to understand if citizens’ opinions influenced the evaluations, recommendations, and contestations based on NIR. Parishes in the municipality of Valongo were selected and analysed, namely Alfena, Campo e Sobrado, Valongo, and Ermesinde; a total of 998 questionnaires were collected. It was concluded that all of the studied dimensions were statistically significant in the final structural estimated model. The structural results point to municipal satisfaction and contestations and complaints of municipal executives as having directly positive and statistically significant influences on NIR. Organizational performance and perceived quality have directly positive but not statistically significant influences on NIR. The results of this research suggest that obtaining the personal opinions of citizens (e.g., regarding the work performances of their mayors) allows citizens to feel heard and active in their municipalities. From the point of view of public executives, the results of this type of study could provide valid information that allows stakeholders to make political decisions that are appropriate for the interests of their communities (e.g., by listening to their citizens).

O9-3 Reducing workplace sedentary behaviour: An exploration of the facilitators and barriers to professional men reducing prolonged sedentary behaviour

IntroductionThere is a growing interest in workplace interventions to reduce sedentary behaviour. Professional males are most at risk of prolonged sedentary behaviour, are considered difficult to reach in terms of recruitment to studies, and may require targeted health promotion interventions. Research on the views of senior managers and executives as well as employees in a professional setting in relatively underdeveloped. Studies have shown that a ?one size fits all' approach is not suitable in behaviour change interventions. The aim of this study was to qualitatively explore professional male workers' facilitators and barriers to reducing workplace sedentary behaviour and their views on suggested intervention strategies to ensure relevance and practicality of the intervention in each specific context.MethodsThree semi-structured focus groups and one interview were conducted with a purposive sample of 25 professional men (15 employees and 10 senior managers). The men were recruited using convenience sampling from two professional worksites in Dublin, Ireland. Transcripts were analysed using thematic analysis.ResultsThe men identified a range of intrapersonal, interpersonal and organisational barriers and facilitators to reducing workplace sedentary behaviour. Perceived facilitators included individual motivation, the formation of new habits likely through small changes, management buy-in and support and organisational culture. Perceived barriers included the primacy of work, job requirements of being desk-bound, and management expectations. Views of suggested strategies for a novel multicomponent intervention to target the determinants of sedentary behaviour as informed by the socio-ecological model were positive overall.ConclusionsThe needs, preferences and opinions of professional men to participate in a workplace intervention to reduce sedentary behaviour should be taken into consideration prior to implementation in a workplace setting. This is important to ensure relevance and the practicality of intervention strategies in the particular settings.

The relative merit of two segmentation approaches: executives views and a cost-benefit analysis

PurposeThis study aims to capture the views of executives about the merit of using the two segmentation approaches (quantitative vs qualitative). Furthermore, this study aimed to examine costs and benefits for two different segmentation approaches, using a minimax simple cost-benefit analysis (CBA) matrix.Design/methodology/approachA total of 16 semistructured interviews were conducted with executives within the University of Sharjah (UoS). Furthermore, a minimax approach was applied to the CBA study.FindingsEvidence in this study found that the financial cost of quantitative segmentation approaches was higher than qualitative approaches. However, the decision-makers trusted the quantitative approach more regardless of the incurred costs. The study also found that there was a limited knowledge about social marketing and segmentation among executives.Research limitations/implicationsLimitations of this study relate to the methodology applied, the sample selected and the lead research. Another factor is selection bias, which limited this study to one organization’s executives. It is conceivable that middle-level management would have had the desire to participate because they make the recommendations to top management in decision-making. The researcher did not collect precise data on time taken to design, implement and analyses the two segmentation studies, which qualified the precision of the CBA. Also, the fact that the sample includes participants from a relatively narrow range of disciplines should be noted as a limitation of the study.Practical implicationsThe current study provides a case study demonstrating how CBA provides a dollar amount estimate permitting alternate segmentation approaches to be compared and contrasted, assisting in the value estimation of any social marketing project.Social implicationsThe paper draws upon two streams of the literature: social marketing and CBA. The paper focused on the understanding of the literature, CBA offers a technique applicable to demonstrating cost savings that can be derived from choosing one method over another. Moreover, CBA assists in understanding the benefits or potential opportunity cost both financially and nonfinancially.Originality/valueThis paper presents one of the first studies conducting a CBA to compare and contrast two segmentation approaches in social marketing. The study provides interesting insights into the perceptions of management executives over alternative research methods, although the results are limited to a case study.

Accelerating Virtual Health Implementation Following the COVID-19 Pandemic: Questionnaire Study.

BackgroundThe COVID-19 pandemic accelerated drivers for virtual health adoption and triggered the US federal government to implement regulatory changes to reduce barriers to virtual health implementation. Consequently, virtual health solutions have been increasingly adopted, and health systems in the United States have been reorganizing their care delivery process with unprecedented speed.ObjectiveThis study aimed to assess and make recommendations on the strategy, business model, implementation, and future considerations for scaling and sustaining virtual health solutions based on the views of executives from the largest health systems in the United States.MethodsIn September 2020 and October 2020, the Health Management Academy conducted 29 quantitative surveys and 23 qualitative interviews involving 58 executives from 41 of the largest health systems in the United States. Participating health systems were approximately equally distributed across size categories (small, medium, and large, defined as annual total operating revenue US $2-3 billion, $3-6 billion, and >$6 billion, respectively) and US Census Bureau regions (Northeast, Midwest, South, and West).ResultsBased on the Health Management Academy’s assessment of approaches to governance, financing, data infrastructure, and clinical integration of virtual health, most participating health systems (13/24, 54%) had a mid-stage level of maturity in virtual health implementation. Executives reported the pandemic is forcing health systems to re-examine strategic priorities; the most commonly raised key impacts were increased access (15/21, 71%) and flexibility (10/21, 48%) as well as lower costs of care delivery (9/21, 43%). Most executives (16/28, 57%) reported their organization had a defined budget for virtual health, and many noted that virtual health is best supported through value-based payment models. Irrespective of health system maturity, reimbursement was consistently rated as a key challenge to virtual health scaling, along with patient access to and understanding of virtual health technology. The success of virtual health implementation was most commonly measured by patient satisfaction, health care provider engagement, and proportion of health care providers using virtual health solutions (reported by 7/8, 88%; 6/8, 75%; and 7/8, 75% of information technology executives, respectively). Almost all health systems (27/29, 93%) expect to continue growing their virtual health offerings for the foreseeable future, with user-friendliness and ease of integration into the electronic medical record as key factors in making go-forward decisions on virtual health solutions (each selected by 9/10, 90% executives).ConclusionsThe increased demand for virtual health solutions during the COVID-19 pandemic is expected to continue postpandemic. Consequently, health systems are re-evaluating their current platforms, processes, and strategy to develop a sustainable, long-term approach to virtual health. To ensure future success, health system leaders need to proactively build on their virtual health solutions; advocate for payment, site flexibility, and reimbursement parity for virtual health; and demonstrate continued engagement and boldness to evolve care beyond established models.

Digitalization-enabled evolution of customer value creation: An executive view in financial services

Digitalization and related transformation in services is disrupting existing businesses and changing the positions and roles of incumbent and new players in the industry, as well as customers. This study aims to create an understanding of how digitalization has driven change in customer value creation, and how companies can enhance customers’ digital value creation in the present situation. For this purpose, we conduct a qualitative inquiry and use inductive logic with rich data from the represented industry – the financial sector – which enables us to detect the evolution of value creation during the last thirty years from an executive perspective. Our contribution is based on defining change processes involved in the evolution of customer value creation due to digitalization and revealing its microfoundations.

Performance evaluation of complex multi-thread applications through execution path analysis

The sporadic latency problems of multi-threaded applications remain a major concern for developers. A performance issue may be caused by internal factors such as an error in the code, inadequate database design or external factors such as thread imbalances, resource contention or system overload. In complex applications such as the Chromium browser, which is our focus in this paper, being able to collect precise unified information from several layers of the application or system is the first challenge. There exists a built-in tracer for Chromium, however, it provides a limited view of the application execution. The correlated analysis of the data collected from the multiple execution levels of the application is another challenge. In this paper, after explaining our tracing method for collecting data from the application and the operating system kernel simultaneously, we translate the multi-level tracing data into a unified model. We then use this model to perform kernel-level control flow analysis for user-level browser actions, to detect latency issues and identify their main causes. We show the effectiveness of the proposed method by detecting three Chromium performance bugs and finding their root-causes. Although our use-cases are based on the Chromium browser, the proposed method and lessons learned could be adapted for analysis of other complex multi-threaded applications.

Chief Executive's View: Climate change, The Society's COP26 Hub and physiology

Chief Executive's View: Climate change, The Society's COP26 Hub and physiology

Executive Views on Organizational Health Indicators: A Case Study

Executive Views on Organizational Health Indicators: A Case Study

EtherClue: Digital investigation of attacks on Ethereum smart contracts

Programming errors in Ethereum smart contracts can result in catastrophic financial losses from stolen cryptocurrency. While vulnerability detectors can prevent vulnerable contracts from being deployed, this does not mean that such contracts will not be deployed. Once a vulnerable contract is instantiated on the blockchain and becomes the target of attacks, the identification of exploit transactions becomes indispensable in assessing whether it has been actually exploited and identifying which malicious or subverted accounts were involved. In this work, we study the problem of post-factum investigation of Ethereum attacks using Indicators of Compromise (IoC) specially crafted for use in the blockchain. IoC definitions need to capture the side-effects of successful exploitation in the context of the Ethereum blockchain. Therefore, we define a model for smart contract execution, comprising multiple abstraction levels that mirror the multiple views of code execution on a blockchain. Subsequently, we compare IoCs defined across the different levels in terms of their effectiveness and practicality through EtherClue, a prototype tool for investigating Ethereum security incidents. Our results illustrate that coarse-grained IoCs defined over blocks of transactions can detect exploit transactions with less computation. However, they are contract-specific and suffer from false negatives. On the other hand, fine-grained IoCs defined over virtual machine instructions can avoid these pitfalls at the expense of increased computation, which is nevertheless applicable for practical use.

Digitalization-Enabled Evolution of Customer Value Creation: An Executive View in Financial Services

Digitalization-Enabled Evolution of Customer Value Creation: An Executive View in Financial Services