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The purpose of this paper is to quantitatively analyse the changes in the functional efficiency of the six Chinese agricultural futures markets and compare the relative behaviour of different futures markets. In addition, this paper analyses the causes of differences in the functional efficiency of agricultural futures markets and advances policy suggestions.

The method used in this paper is the social loss index proposed by Stein (1981, 1986). This method can quantitatively measure the functional efficiency of agricultural futures markets from the perspective of social welfare. The indicator is calculated for the 2009–2017 period and for several sub-periods. The data are from the CSMAR research data services in China.

Preliminary results suggest that the longer it takes for an agricultural futures contract to reach maturity, the lower the functional efficiency of its market. Second, the functional efficiency of the agricultural futures markets in China is improved except for that of the wheat futures market. Finally, the corn futures market is most efficient probably due to the progress of marketization, while the strong wheat futures market is most inefficient probably due to the decrease in futures market liquidity.

This paper uses a more reasonable method to study the functional efficiency of Chinese agricultural futures markets and then analyses the causes of differences in the functional efficiency of agricultural futures markets.

The purpose of the paper is to examine China's county‐level fiscal difficulties. A large portion of China's counties (county‐level cities) have to run with the shortage of financial resources and huge government debt. To make a suitable policy to solve this problem is a top priority.

Using the first‐hand survey data, the paper compares nine sample counties whose economic development level is different, sums up the difficulties county‐level governments are facing and explores countermeasures from qualitative and quantitative approaches.

By studying the survey data of nine sample counties (cities), it is found that county‐level finance is facing the following problems: low‐level fiscal revenue, high debt risk and large gap of fiscal revenue between different counties (cities). Based on these findings, the paper provides suggestions such as ensuring that the county‐level government has sufficient fiscal resources and improving the transfer payment system.

Data from three well‐developed counties (county‐level cities), three middle‐income counties (county‐level cities) and three backward counties made the paper's findings more comprehensive and realistic and suggestions more practical.

The food industry is crucial in delivering healthy products for life saving of the society. The identification of key barriers of knowledge management (KM) is desired to enhance the sustainability of the industry. KM has been seen as a part of sustainable development by reducing the bullwhip effect in the entire supply chain. The core objective of the existing research is to prioritize the essential factors of KM adoption in sustainable supply chain (SSC) based on fuzzy analytical hierarchy process (FAHP) method.

In order to fulfill objectives of this study, an extensive review of literature and a questionnaire-based field visits were conducted. A total of five major barriers categories and 22 sub-barriers categories were identified in food sector of Pakistan using experts' inputs. This study employed fuzzy analytical hierarchy process (FAHP).

Managerial barriers, innovation and technological barriers categories are found to be highly prioritized among others. Further, the sensitivity analysis is applied to check the incremental changes of ranked barriers. This prioritization of barriers and incremental changes in them is expected to serve food sector for long-term sustainability and competitive advantage for importers and exporters. Finally, the findings of this research are very helpful for industrial experts, practitioners, consultants and government officials in effectively developing policies regarding KM adoption in line with sustainable goals.

The present work is conducted in the Pakistani context; however, the benchmark model may be tested and applied to other developing countries to compare the outcomes. For further research, the identified barriers may also be evaluated to establish their inter-relationships, using ISM, DEMATEL, ANP, etc. Similarly, the results of this study can also be compared with that of other fuzzy multi-criteria techniques like fuzzy TOPSIS, fuzzy VIKOR, fuzzy ELECTRE, fuzzy PROMETHEE, or fuzzy VIKOR.

This research study can facilitate policymakers, government bodies, stakeholders and supply chain professionals to recognize the key barriers they may encounter in adopting KM practices in their SSC. Additionally, this work helps managers to evaluate the identified barriers by computing their relative importance in adopting KM practices at managerial levels like strategically, tactically and operationally activities in business. This study also facilitates industrial management in formulating policies and action plans in case of implementation, eliminating the barriers in adoption of KM, and SSC successfully.

Few research studies were conducted on KM adoption in industries of China, India, Turkey, Saudi Arabia and Malaysia, but due to workforce diversity these industries have dissimilar views of experts about KM adoption. This study significantly contributed to fill the existing literature gap for prioritization of key barriers against KM implementation in Pakistani context.