The Development of Quality Management in China: Case Studies of Small-Sized Manufacturing POEs in Hebei

“Made in China” has attracted the whole world’s attention because of its large quantity and the endless quality incidents. Several researchers have already made the studies of the quality management development of the whole China or the business centers, for example Shanghai and Hong Kong. However, very limited attention was paid to the quality management in less developed region of China. Therefore, with the interest of the quality management development in the less developed region and edge cities, this dissertation represents the research of quality management development of small-sized manufacturing POEs in Hebei Province. The objectives of this dissertation are to realize the development process of quality management, to highlight the quality management practice, to point out the quality management problems, to conclude the common barriers in quality management development, and to provide practical suggestions of quality management development for small-sized manufacturing POEs in Hebei. The research was supported by the case studies of small-sized manufacturing POEs in Hebei. 4 companies were observed and the owner, quality manager and worker of each company were interviewed in order to obtain the information about the quality management development. Through the 4 case studies, the problems in quality management were analyzed and the 5 common barriers which impeded the quality management development of small-sized manufacturing POEs in Hebei were concluded and discussed. The 5 common barriers were the local employee problems, owner and mangers problem, limited growth opportunity, misunderstanding of ISO 9000 certificates and loose government supervision. The reasons and influences of each common barrier were analyzed in detail. It was found that some of the quality management problems which were discovered in 1990s still existed in small-sized manufacturing POEs in Hebei. This reflected the quality management development of small-sized manufacturing POEs in Hebei was slow. The findings in this dissertation can provide meaningful supplements to help draw a more comprehensive blueprint of China’s quality management development. In addition, the dissertation still faced several limitations. First, the small sample size weakened the generality of the findings. Second, due to the protection of the business secret, the quality data and product design process were not exposed to the author. Therefore, the analyses of the quality management performance were not complete as excepted. Third, without the comparison between different ownerships, the characters of quality management development of small POEs were not obvious. These limitations should be compensated in the future research

Examining supply chain quality management in the Chinese automobile industry

The aim of this thesis is to understand what supply chain quality management (SCQM) is and to examine SCQM practices in the Chinese automobile industry by comparing the different SCQM implementation between Chinese Self-owned Brands (CSBs) and Joint Ventures (JVs). This thesis attempts to reveal and understand SCQM practices in order to provide new insights in dealing with quality issues along the supply chain. Hence, in this thesis three research questions (RQs) are explored and answered: RQ1) What are the main factors impacting on SCQM in the Chinese automobile industry? RQ2) What are the differences between CSBs and JVs in the field of SCQM? RQ3) Why do such differences occur? A mixed research methodology was implemented to answer these three RQs. First, a case study in seven Chinese automobile companies was conducted. Resulting from this qualitative method, this research proposes a robust SCQM framework and generates SCQM measurements. SCQM is conceptualised as a multidimensional construct and the framework is composed of companywide quality management, supplier-side SCQM, customer-side SCQM, and performance. The measurement model evaluation, structural model evaluation, and multigroup analysis were conducted in sequence to investigate multi-dimensionality of SCQM, test the relationships among these dimensions, and clarify the different SCQM between CSBs and JVs. Variance-based structural equation modelling of Partial Least Square (PLS) on the platform of Smart-PLS 3.0 was used to analyse the 196 quantitative data that were collected from CSBs and JVs. Further, six follow-up interviews were then conducted to identify the root causes of the findings of the survey study. This research finds that companywide quality management cannot directly influence operational performance due to the complexity of China’s automobile supply chain. It illustrates that customer-side SCQM practices have the most significant influence on operational performance. This study also clarifies that ownership bears a critical impact on the relationship between customer-side SCQM practices and operational performance. It extends the SCQM literature by studying a large number of automobile companies in China and comparing the different supply chain level quality practices between CSBs and JVs. It provides good breadth to the literature by answering the calls for ownership and emerging market research. This thesis also enhances the understanding of managers about the best SCQM practices to assist companies in moving from their current practices to their preferred one. It also illustrates significant directions for supply chain level quality system designs for automobile companies

Maximising the Circular Economy and Sustainability Outcomes: An End-of-life Tyre Recycling Outlets Selection Model

The increasing concern for sustainability and longing for the transition into the circular economy has fostered an immense interest in re-configuring the end-of-life tyre supply networks. However, the existing literature is incapable of providing sufficient guidance in regard to the allocation of end-of-life tyre among recycling outlets to maximise the circular economy and sustainability outcomes. Hence, this study aims to propose a comprehensive list of evaluation criteria to rank recycling outlets, and develop an end-of-life tyre outlets selection matrix. A hybrid method is proposed by integrating fuzzy Analytical Hierarchy Process, fuzzy Technique of Order Preference Similarity to the Ideal Solution, the multi-objective linear programming, and semi-structured interviews. By analysing the empirical data collected from one of the largest European collectors, this study reveals that cement manufacturing, which is the primary recycling outlet, ranks the lowest among the five recycling outlets in terms of the circular economy and sustainability outcome. Nevertheless, synthetic turf manufacturing and moulded objects manufacturing rank the highest in the circular economy and sustainability outcomes, respectively. It is proved that cost and profit are key drivers for recycling outlets selection, subjected to end consumers’ perceptions and the ease of end-of-life tyre processing. The ranking and the performance of recycling outlets also signify the competitive relationship between the circular economy and sustainability as excelling in the circular economy outcome would trade-off sustainability performance

Investigating the effect of carbon tax and carbon quota policy to achieve low carbon logistics operations

Developing a low-carbon economy and reducing carbon dioxide emission have become a consensus for both academics and practitioners. However, the existing literature did not pay enough attention in interrogating the impacts of Carbon Tax (CT) and Carbon Quota (CQ) policy on distribution costs and carbon dioxide emission in the field of vehicle routing problem. Moreover, the investigated subsidies factor is also incomplete. This research stands on the position of the company to study the impact of CT and CQ policy on aforementioned two aspects. A mathematical model is developed to achieve the best low carbon vehicle routing under the optimal policy. The optimization goal of this research is to minimize the total cost that includes vehicle-using, transportation, CT, CQ, and raw material subsidy costs. An improved optimization algorithm, namely Genetic Algorithm-Tabu Search (GA-TS), is proposed to solve a given business case. In the simulation experiments, GA-TS and a traditional GA are compared and the results show the advantage of GA-TS on reducing the total cost and carbon dioxide emission. Furthermore, the experiments also explore the total cost and carbon dioxide emission under three scenarios (Benchmark, CT and CQ), incorporating four policies: CT, Carbon Tax Subsidy (CTS), CQ, and Carbon Quota Subsidy (CQS). It is concluded that CQS is the ideal policy to minimize distribution cost and carbon dioxide emission. In addition, the impact of vehicles’ capacities on the total cost and carbon dioxide emission is also analyzed in this research. This research also aimed at assisting practitioners in better formulating delivery routes, as well as policy makers in developing carbon policies. Finally, the limitations and the future research directions of this research are also discussed

Vehicle Routing Problem in Cold Chain Logistics: a Joint Distribution Model with Carbon Trading Mechanisms

Fierce competition and the mandate for green development have driven cold chain logistics companies to minimize total distribution costs and carbon emissions to gain a competitive advantage and achieve sustainable development. However, the cold chain logistics literature considers carbon trading mechanisms in sharing economy, namely the joint distribution, is limited. Our research builds a Joint Distribution-Green Vehicle Routing Problem (JD-GVRP) model, in which cold chain logistics companies collaborate among each other to deliver cold chain commodities by considering carbon tax policy. Based on the real business data from four cold chain companies and 28 customers, a simulated annealing (SA) algorithm is applied to optimize the model. The results indicate that joint distribution is an effective way to reduce total costs and carbon emissions when compared with the single distribution. The total cost is positively correlated with the carbon price, while the carbon emissions vary differently when the carbon price increases. In addition, carbon quotas have no effect on the delivery path. This research expands cold chain logistics literature by linking it with joint distribution and carbon trading mechanisms. Moreover, this research suggests that cold chain logistics companies could enhance delivery efficiency, reduce the business cost, and improve competitiveness by reinforcing the collaboration at the industry level. Furthermore, the government should advocate the mode of joint distribution and formulate an effective carbon trading policy to better utilize social and industrial resources to achieve the balanced economic and environmental benefits

Do green practices really attract customers? The sharing economy from sustainable supply chain management perspective

The notion of the sharing economy has been introduced in many sectors and provided significant benefits to consumers and asset owners. Despite the remarkable improvement of the sharing economy in recent years, its relationship with sustainability remains insufficiently researched. This study adopts a sustainable supply chain management (SSCM) perspective. A large-scale survey with 420 participants showed that investment recovery (IR) practices and corporate social responsibility (CSR) conducted by sharing economy platforms significantly and positively affect customers’ intention to use sharing economy-based services/products, whereas internal green management (IGM), supplier green management (SGM), eco-design (ECD) and customer green management (CGM) practices do not. A follow-up qualitative study with ten participants provided further explanations and supported the findings of the survey. This study links the sharing economy and sustainability by testing the effectiveness of sharing economy platforms’ sustainable practices and proposes the best practices for sharing economy platforms to maintain a long-term sustainable marketplace

Nonparametric decentralized detection based on weighted count kernel

Mankind faces major challenges in the area of food safety and food security. In addition to the growing population, urbanization, climate change, global environmental change and economic inequality, as well as instability, have a major impact on balanced food supply. According to the WHO (2018) study, not only the elimination of hunger is a problem, but also the increase of our well-being. While 0.8 billion people suffer from a lack of available food, 33% of the global population is overweight, 30% of them are obese. In a long term our growing well-being can also be a great problem. There are three types of dietary problems that coexist in parallel: the hunger and malnutrition, the microelement deficiency, and excessive nutrition and obesity. These three health problems represent a serious burden on public health, which has to be considered in the context of food security and food safety.Az élelmiszer- és élelmezésbiztonság területén számos kihívás vár az emberiségre. A népesség növekedése mellett az urbanizáció, az éghajlatváltozás, a globális környezeti változások és a gazdasági egyenlőtlenség, valamint az instabilitás is nagymértékben befolyásolja a kiegyensúlyozott élelmiszerellátást. A WHO (2018) tanulmánya alapján elmondható, hogy nem csak az éhezés felszámolása jelent problémát, hanem a jólétünk fokozódása is. Miközben 0,8 milliárd ember attól szenved, hogy nincs számára elérhető elegendő élelmiszer, addig a globális népesség 33%-a túlsúlyos, amiből 30% elhízott. Hosszú távon tehát fokozódó jólétünk is egyre nagyobb problémát okozhat. Háromféle, egymással párhuzamosan létező, mégis összefüggő táplálkozási problémát kell kiemelni: ezek az éhezés és az alultápláltság, a mikroelem-hiány, továbbá a túlzott mértékű táplálkozás és elhízás. Ez a három egészségügyi probléma a közegészségügyre nézve jelent komoly terheket, amelyet a táplálkozás biztonságával és az élelmiszerbiztonsággal összefüggésben kell vizsgálni

Toward Sustainability:Using Big Data to Explore Decisive Supply Chain Risk Factors Under Uncertainty

Rapid market changes aimed at sustainability have led to supply chain risks and uncertainties in the Taiwanese light-emitting diode industry. These risks and uncertainties can be captured by social media, quantitative and qualitative data (referred to herein as big data), but the industry has been unable to manage this information boom to respond to customer needs. These various types of data have their own characteristics that affect decision making about developing firm capabilities. This study aggregates the various data to undertake an extensive investigation of supply chain risks and uncertainties. Specifically, this study proposes using the fuzzy and grey Delphi methods to identify a set of reliable attributes and, based on these attributes, transforming big data to a manageable scale to consider their impacts. Subsequently, both the fuzzy and grey Decision Making Trial and Evaluation Laboratories applied to determine the causal relationships for supply chain risks and uncertainties. The results reveal that capacity and operations have greater influence than other supply chain attributes and that risks stemming from triggering events are difficult to diagnose and control. The implications, conclusions and findings are addressed

Karst collapse risk zonation and evaluation in Wuhan, China based on analytic hierarchy process, logistic regression, and insar angular distortion approaches

The current study presents a detailed assessment of risk zones related to karst collapse in Wuhan by analytical hierarchy process (AHP) and logistic regression (LR) models. The results showed that the LR model was more accurate with an area under the receiver operating characteristic (ROC) curve of 0.911 compared to 0.812 derived from the AHP model. Both models performed well in identifying high-risk zones with only a 3% discrepancy in area. However, for the medium-and low-risk classes, although the spatial distribution of risk zoning results were similar between two approaches, the spatial extent of the risk areas varied between final models. The reliability of both methods were reduced significantly by excluding the InSAR-based ground subsidence map from the analysis, with the karst collapse presence falling into the high-risk zone being reduced by approximately 14%, and karst collapse absence falling into the karst area being increased by approximately 6.5% on the training samples. To evaluate the practicality of using only results from ground subsidence maps for the risk zonation, the results of AHP and LR are compared with a weighted angular distortion (WAD) method for karst risk zoning in Wuhan. We find that the areas with relatively large subsidence horizontal gradient values within the karst belts are generally spatially consistent with high-risk class areas identified by the AHP-and LR-based approaches. However, the WAD-based approach cannot be used alone as an ideal karst collapse risk assessment model as it does not include geological and natural factors into the risk zonation. © 2021 by the authors. Licensee MDPI, Basel, Switzerland