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Looks at consumer research in Greater China including Mainland China, Hong Kong and Taiwan. Maps out the contributions within this area and guides future research. Examines the state of the art over the 1979‐97 period, with particular emphasis on the topics that have been researched, the extent of the theory development in the field and the methodologies used in conducting research. Uses content analysis to review 75 relevant articles. Suggests that, while a considerable breadth of topics have been researched, there remains much to be done, there is further room for theoretical development in Chinese consumer behaviour studies; and the methodologies used need improvement and further refinement.

The purpose of this study is to present a newly proposed and developed sorting algorithm-based merging weighted fraction Monte Carlo (SAMWFMC) method for solving the population balance equation for the weighted fraction coagulation process in aerosol dynamics with high computational accuracy and efficiency.

In the new SAMWFMC method, the jump Markov process is constructed as the weighted fraction Monte Carlo (WFMC) method (Jiang and Chan, 2021) with a fraction function. Both adjustable and constant fraction functions are used to validate the computational accuracy and efficiency. A new merging scheme is also proposed to ensure a constant-number and constant-volume scheme.

The new SAMWFMC method is fully validated by comparing with existing analytical solutions for six benchmark test cases. The numerical results obtained from the SAMWFMC method with both adjustable and constant fraction functions show excellent agreement with the analytical solutions and low stochastic errors. Compared with the WFMC method (Jiang and Chan, 2021), the SAMWFMC method can significantly reduce the stochastic error in the total particle number concentration without increasing the stochastic errors in high-order moments of the particle size distribution at only slightly higher computational cost.

The WFMC method (Jiang and Chan, 2021) has a stringent restriction on the fraction functions, making few fraction functions applicable to the WFMC method except for several specifically selected adjustable fraction functions, while the stochastic error in the total particle number concentration is considerably large. The newly developed SAMWFMC method shows significant improvement and advantage in dealing with weighted fraction coagulation process in aerosol dynamics and provides an excellent potential to deal with various fraction functions with higher computational accuracy and efficiency.

The purpose of this paper is to study the evolution and growth of aerosol particles in a turbulent planar jet by using the newly developed large eddy simulation (LES)-differentially weighted operator splitting Monte Carlo (DWOSMC) method.

The DWOSMC method is coupled with LES for the numerical simulation of aerosol dynamics in turbulent flows.

Firstly, the newly developed and coupled LES-DWOSMC method is verified by the results obtained from a direct numerical simulation-sectional method (DNS-SM) for coagulation occurring in a turbulent planar jet from available literature. Then, the effects of jet temperature and Reynolds number on the evolution of time-averaged mean particle diameter, normalized particle number concentration and particle size distributions (PSDs) are studied numerically on both coagulation and condensation processes. The jet temperature and Reynolds number are shown to be two important parameters that can be used to control the evolution and pattern of PSD in an aerosol reactor.

The coupling between the Monte Carlo method and turbulent flow still encounters many technical difficulties. In addition, the relationship between turbulence, particle properties and collision kernels of aerosol dynamics is not yet well understood due to the theoretical limitations and experimental difficulties. In the present study, the developed and coupled LES-DWOSMC method is capable of solving the aerosol dynamics in turbulent flows.

In this research, collaboration attributes related to the firm's intrinsic and extrinsic facets at pertinent levels (i.e. enterprise, strategic, operational, and tactical levels) for construction equipment OEMs (original equipment manufacturers) operating in India have been quantified and modeled.

For modeling the intra-firm collaboration at respective organizational levels, relevant attributes have been populated employing literature review followed by subsequent validation from pertinent focus groups. The focus groups comprising professionals working in the construction and mining equipment industry in India aided us in estimating the extent of interdependencies and influences within/amongst collaboration attributes. The collaboration attributes and respective interdependencies/influences are modeled employing the concept of graph theory wherein the individual attributes are represented using vertices and influences/interdependencies are represented using edges. The collaboration indices resulting from the variable permanent matrix have been derived as well.

Scenario and subsequent sensitivity analysis are performed. This research discusses the significance and aspects related to various collaborative attributes and the interrelations amongst them. Further, the research also evolves quantitative measures of collaboration indices at enterprise, strategic, tactical and operational levels by employing a graph-theoretic approach (GTA). The authors have also extricated and discussed a number of meaningful implications from both the perspectives of interorganizational relationships (IORs) and the normative theory of organizations using a cross-case analysis of five firms having operations in India.

The research would aid organizations (particularly those belonging to the construction equipment sector) measure the efficacy of collaboration in respective value-chains at strategic, tactical and operational levels. From the theoretical perspective, the integration of the IORs and normative theory of organizations enables looking at the intra-firm collaboration problem from a multi-dimensional standpoint involving activities, performance measures, action initiation, communication, shades of top management, level of activity, etc.

The world consists of diverse and distinctive economic systems. Due to the unique historical, cultural and location-specific contexts embedded in each economy, a comparison of strategic behaviors across economies is unlikely to provide a causal estimate of the influence of these contextual factors on strategy–performance relationships. In this paper, I outline three approaches to researching multinational firms that address this dilemma. They include the multilevel, historical and variance-centered perspectives, all of which can help international-business (IB) researchers develop stronger theoretical foundations from which to explain why country-specific contexts matter in designing IB action and research.

Presents a portfolio model for multi‐sales channel effort deployment. Shows how the approach can help sales management restructure sales channels. Notes that combining an organization′s selling effort into multiple sales channels can be facilitated through an analytical approach that considers variations in customer requirements, buying power and contact costs. Concludes that implementing a successful multiple sales channel strategy offers impressive productivity opportunities.

This paper aims to build a novel model and approach that assist an aircraft MRO procurement and overhaul management problems from the perspective of aircraft maintenance service provider, in order to ensure its smoothness maintenance activities implementation. The mathematical model utilizes the data related to warehouse inventory management, incoming customer service planning as well as risk forecast and control management at the decision-making stage, which facilitates to alleviate the negative impact of the uncertain maintenance demands on the MRO spare parts inventory management operations.

A stochastic model is proposed to formulate the problem to minimize the impact of uncertain maintenance demands, which provides flexible procurement and overhaul strategies. A Benders decomposition algorithm is proposed to solve large-scale problem instances given the structure of the mathematical model.

Compared with the default branch-and-bound algorithm, the computational results suggest that the proposed Benders decomposition algorithm increases convergence speed.

The results among the same group of problem instances suggest the robustness of Benders decomposition in tackling instances with different number of stochastic scenarios involved.

Extending the proposed model and algorithm to a decision support system is possible, which utilizes the databases from enterprise's service planning and management information systems.

A novel decision-making model for the integrated rotable and expendable MRO spare parts planning problem under uncertain environment is developed, which is formulated as a two-stage stochastic programming model.

This paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.

An integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.

The ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.

This paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.

It provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.

Public–private partnerships (PPPs) are viewed as a reform tool for resolving inefficiency and absence of dynamism in water supply delivery in developing countries. However, the requirements for their successful implementation have received very little attention. This paper aims to describe a set of critical success factors (CSFs) that, when given special and continual attention, would ensure a successful project implementation and to provide a predictive tool to aid implementers to evaluate the likelihood of a successful PPP water supply project.

Fourteen perceived CSFs were initially derived from project cases and extant literature, and verified through a two-round Delphi survey. Factor analysis established five critical success factor groups (CSFGs) that were then used to develop a fuzzy synthetic evaluation tool for assessing the chance of a successful project.

The five key CSFGs are commitment of partners, strength of consortium, asset quality and social support, political environment, and national PPP unit. The model output showed that, overall, these factors have a “very high” positive impact on a successful implementation of a water supply project. Hence, there is an excellent correlation between achievement of the CSFGs and project success. Success indices of individual principal factors are also “very high”.

The study presents a tool to public clients and private audience, and it is hoped that the study will trigger policy development towards PPP practice in developing countries, because these findings have wider implications for legal and regulatory systems, public capacity, financing, public procurement and politics.