Capturing the benefits of industry 4.0: a business network perspective

Abstract

This study uses a business network perspective to investigate the industry 4.0 context with the internet of things (IoT) as its enabling technology and product-use data as its core network resource. A three-stage qualitative methodology (interviews, focus group, Delphi-based inquiry) was used to examine the case of an emergent IoT-based business network in the UK road transport industry to examine: (i) how aspects of product use data influence the benefit opportunities the data provide to the different network actors; (ii) how capturing of the benefit opportunities in a network context is impacted by key barriers; and (iii) how network capabilities can overcome these barriers to capture benefits from product-use data. The study, thereby, contributes to an understanding of the industry 4.0 context from a resource dependency theory perspective and provides concrete recommendations for management operating in this context.     

A simulation testing and analysis of aggregate production planning strategies

In this study, a hybrid discrete event simulation (DES) and system dynamics (SD) methodology is applied to model and simulate aggregate production planning (APP) problem for the first time. DES is used to simulate operational-level and shop-floor activities incorporated into APP and estimate critical time-based control parameters used in SD model of APP and SD is used to simulate APP as a collection of aggregate-level strategic decisions. The main objective of this study is to determine and analyse the effectiveness of APP strategies regarding the Total Profit criterion by developing a hybrid DES–SD simulation model for APP in a real-world manufacturing company. The simulation results demonstrated that the priority of APP strategies with regards to Total Profit criterion is: (1) the pure chase strategy, (2) the modified chase strategy, (3) the pure level strategy, (4) the modified level strategy, (5) the mixed strategy and (6) the demand management strategy, respectively. The APP system is first simulated under mixed strategy (basic scenario) conditions to include all APP capacity and demand options in constructed SD simulation model to show a comprehensive view of APP components and their interdependent interactions. Then, the obtained results will be used as Total Profit measure to compare with system's performance under some experimental scenarios applying different APP strategies.     

Human resource development competencies as predictors of agricultural extension agents' performance in Yemen

Human resource development (HRD) issue is recognized as a significant factor for survival of organizations and professionals, including those in the sector of agricultural extension. Few empirical studies have examined the influence of HRD competency variables on agricultural extension agents' performance. The authors argue that HRD competency variables such as leadership development, communication, programme planning, programme implementation and programme evaluation could predict agricultural extension agents' performance. Questionnaire data were collected from a sample of 290 extension agents in Yemen to discover if HRD competencies affect the performance of extension agents. Regression analysis shows that three variables – competencies in programme implementation, programme evaluation and programme planning – contributed significantly to the performance of extension agents. These predictors explain 42.2% of the variance in the job performance model.     

An Evaluation of the NERJIT Priority Rule in a Kanban‐Controlled Flowshop

Significant progress in production and information technologies and innovations in management of operations during the last couple of decades have made the production of small lots and deployment of Just‐In‐Time (JIT) concepts in flowshops possible. As a result, some researchers and practitioners have been seeking to improve the performance of non‐repetitive systems using JIT concepts. In this process, the JIT concepts that were originally designed for mass production have been modified to adapt JIT to non‐repetitive systems. This article uses a priority rule that is based on real‐time demand and production information for sequencing jobs in a kanban‐controlled flowshop. The analysis of the effect of this priority rule; the number of kanbans; the length of the withdrawal cycle; First‐Come, First‐Served (FCFS); and Shortest Processing Time (SPT) on four performance measures—customer wait time, total inventory, input stock‐point inventory, and output stock‐point inventory, shows that the use of this priority rule results in a significant reduction of customer wait time and a slight decrease in inventory.     

Organizational Factors Affecting Individuals to Donate to NPOs in the Turkish Context

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - While more and more people have been forced from their homes by natural disasters, wars, and violence, the citizens of the...     

Remittances,growth and poverty: New evidence from Asian countries

The present study re-examines the effects of remittances on growth of GDP per capita using annual panel data for 24 Asia and Pacific countries. The results generally confirm that remittance flows have been beneficial to economic growth. However, our analysis also shows that the volatility of capital inflows such as remittances and FDI is harmful to economic growth. This means that, while remittances contribute to better economic performance, they are also a source of output shocks. Finally, remittances contribute to poverty reduction – especially through their direct effects. Migration and remittances are thus potentially a valuable complement to broad-based development efforts.     

Zakat as a Poverty Reduction Mechanism Among the Muslim Community: Case Study of Bangladesh,Malaysia, and Indonesia

Poverty reduction remains the most important challenge for policy makers in Islamic communities. The World Bank (2010: Poverty profile in Muslim world, from http://www.worldbank.org ) estimates that approximately 3 billion people are living in poverty and 46 million more people will come under the income level of US$1.25 a day due to the recent global economic meltdown and slow economic growth rates. Thirty‐five percent of these people are Muslims from Islamic countries. The global Muslim community has an essential role to play in addressing the injustice of global poverty through zakat. Zakat is an Islamic faith‐based institution and is being underutilized for poverty reduction in many of these poor Muslim countries. Since zakat constitutes one of the pillars of Islam, it is logical to assume that policy makers among Muslims should pay serious attention to it. However, that is not the case for many Muslim countries and this paper will show that not all Muslim countries are seriously applying zakat in its strategy of combating poverty. This paper will specifically examine the role and effect of zakat in three Muslim countries (Bangladesh, Malaysia and Indonesia) providing the facts of countries that practise zakat in comparison with those that do not.     

Transforming the Local Capacity on Natural Disaster Risk Reduction in Bangladeshi Communities: A Social Work Perspective

Bangladesh has been a severe victim of its various sporadic natural disasters—flood, cyclone and storm surge, flash flood, drought, tornado, riverbank erosion, and landslide. Familial and societal lives and security of people are being seriously disturbed by these natural calamities every year. They also bring deadly damage to the economy and general environment of the country. Natural disasters cannot be pre‐empted at all, but their damage can be mitigated with effective responses. Social work has been a profession notably known for its intervention of people's vulnerability to natural and man‐made disasters. This concept paper discusses relevant intervention strategies and approaches to transform the local capacity of communities on natural disaster risk reduction in light of the social work profession.     

On Using Hellinger Distance in Checking the Validity of Dynamic Approximations

The purpose of this article is to provide validation for the approximate algebraic propagation algorithms to accommodate non-Gaussian dynamic processes. These algorithms have been developed to carry out Bayesian analysis based on conjugate forms and presented with detailed examples of response distributions such as Poisson and Lognormal. The validity of the approximation algorithms can be checked by introducing a metric (Hellinger divergence measure) over the distribution of the states (parameters) and use it to judge the approximation. Theoretical bounds for the efficacy of such procedure are discussed.     

Solving Noisy ICA Using Multivariate Wavelet Denoising with an Application to Noisy Latent Variables Regression

A novel approach to solve the independent component analysis (ICA) model in the presence of noise is proposed. We use wavelets as natural denoising tools to solve the noisy ICA model. To do this, we use a multivariate wavelet denoising algorithm allowing spatial and temporal dependency. We propose also using a statistical approach, named nested design of experiments, to select the parameters such as wavelet family and thresholding type. This technique helps us to select more convenient combination of the parameters. This approach could be extended to many other problems in which one needs to choose parameters between many choices. The performance of the proposed method is illustrated on the simulated data and promising results are obtained. Also, the suggested method applied in latent variables regression in the presence of noise on real data. The good results confirm the ability of multivariate wavelet denoising to solving noisy ICA.