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This study aims to examine decision factors for global sourcing, differentiated into transcontinental and continental sourcing to obtain insight into locational aspects of sourcing decisions and global trends. This study analyzed various country perceptions to reveal their influence on sourcing decisions. The country of origin (COO) theory explains why certain country perceptions and images influence purchasing experts in their selection of suppliers.

This study used a two-study approach. In Study 1, the authors conducted discrete choice card experiments with 71 purchasing experts located in Europe and the USA to examine the importance of essential decision factors for global sourcing. Given the clear evidence that location is a factor in sourcing decisions, in Study 2 the authors investigated purchasers’ perceptions and images of countries, adding country ranking experiments on various perceived characteristics such as quality, price and technology.

Study 1 provides evidence that the purchasers’ personal relationship with the supplier plays a decisive role in the supplier selection process. While product quality and location impact sourcing decisions, the attraction of the buying company and cultural barriers are less significant. Interestingly, however, these factors seem as important as price to respondents. This implies that a strong relationship with suppliers and good quality products are essential aspects of a reliable and robust supply chain in the post-COVID-19 era. Examining the locational aspect in detail, Study 2 linked the choice card experiments with country ranking experiments. In this study, the authors found that purchasing experts consider that transcontinental countries such as Japan and China offer significant advantages in terms of price and technology. China has enhanced its quality, which is recognizable in the country ranking experiments. Therefore, decisions on global sourcing are not just based on such high-impact factors as price and availability; country perceptions are also influential. Additionally, the significance of the locational aspect could be linked to certain country images of transcontinental suppliers, as the COO theory describes.

The new approach divides global sourcing into transcontinental and European sourcing to evaluate special decision factors and link these factors to the locational aspect of sourcing decisions. To deepen the clear evidence for the locational aspect and investigate the possible influence of country perceptions, the authors applied the COO theory. This approach enabled authors to show the strong influence of country perception on purchasing departments, which is represented by the locational effect. Hence, the success of transcontinental countries relies not only on factors such as their availability but also on the purchasers’ positive perceptions of these countries in terms of technology and price.

Although growing Internet penetration in the hinterlands has attracted agribusinesses to promote digital platforms, farmers are sceptical about using them. The literature discusses agricultural platforms from the theoretical perspective of technological determinism, where the platforms are developed and promoted by firms in a top-down manner to be accepted by farmers. However, this approach results in poorly configured platforms with limited utility for farmers. It is evident from the existing literature that the mere creation of a platform business is not sufficient to guarantee adoption by users. Hence, this study explores how to make the agricultural platform more attractive for farmers.

The present study is based on a discrete choice experiment performed on 126 Indian farmers using agricultural platforms. The data were analysed using the conditional logistic regression method.

The study suggests that farmers expect government and cooperative entities to be also embedded with the platforms. Complementary features such as prompt service, competitive pricing and farm credit were identified as essential attributes. Further, the platforms should enable smallholders to trade farm produce by providing a mechanism for real-time online nudging and bargaining with buyers.

The study is based on the applications of random utility theory. The research has utility for Agtech managers, cooperative institutions and agricultural policymakers.

This is one of the first studies focussing on agricultural platform design from the farmers' perspective. The study implies that incorporating preferred attributes can help practitioners configure platforms to benefit farmers with prospects concerning farm management decisions.

This paper investigates Chinese agricultural insurance agents willingness to offer (WTO) livestock insurance based on the variations of eight main attributes of livestock insurance.

This study implements discrete choice experiments (DCE) with actual insurance agents who design, sell and operate livestock insurance in China. The choice experiment of this study is based on the D-optimal approach, a six-block design, with 15 cards per block and two choices per card. The sample size was 211. Econometrics results are based on conditional and mixed logit models.

The authors find that the subsidy effect is enormous; a one level increase of subsidy leads to 3.166 times higher probability to offer. This subsidy effect is important as it confirms the endogenous structure between price and quantity in insurance offering, where subsidy does not only incentivize demand but also the supply. Another main factor of insurance investigated is the impact of different coverage types on agents' WTO. The authors find that agents prefer mortality insurance the most, followed by revenue insurance and profit insurance, while Index-Based Livestock Insurance (IBLI) is the least preferred to offer. Agents' knowledge about these newer types of insurance supports their WTO as well; thus, proper education is necessary to promote the more advanced types of livestock insurance.

A limitation is that in the presence of COVID 19, and administrative issues at the local level, the sample was not randomly drawn. Nonetheless, the authors believe that there is enough diversity across participants, insurers and provinces and have done sufficient robustness checks to support results and conclusions.

This study provides further validation for the DCE research method that could potentially be applied to different analyses: using choice experiments to study insurers and reveal their preferences, through combinations of various levels of core attributes for insurance products. The findings and contribution are critical to the reform and improvement of livestock insurance in China and for insurance markets more broadly. The authors find that insurers do not place equal weights or values on insurance product attributes and do not view types of insurance equally. In other words, while farmers may hold different preferences about the type of insurance they demand, the results suggest that insurers also hold preferences in the type of insurance they sell.

So far as the authors are aware, this is the first DCE designed around the supply of insurance products with the subjects being insurance agents, marketers and executives.

This study analyses the future job characteristics that are preferred by economics and business administration students in three specific regions of Spain, Colombia and Ecuador, and estimates their willingness to accept each.

A discrete choice experiment (DCE) is carried out in these three regions. The econometric approach is based on the Random Parameter Logit model, which accounts for both the observed and unobserved heterogeneity by the use of socio-demographic variables and correlated random parameters.

The main conclusions indicate that the most important job characteristic for students in all three countries is the long-term career prospects at the company, while a permanent contract is one of the least important job attributes. Regarding the more specific conclusions related to each country, the Ecuadorian students seem to have a higher preference for training opportunities, given the strong relationship between the level of education and the job category. The Spanish students seem to value their commuting time more highly than the South American students.

To authors’ best knowledge, this is the first DCE-based study of economics and business administration students’ preferences for future jobs that has been conducted simultaneously in three countries on two different continents. Furthermore, this study presents fresh cross-country data that allow authors to compare student choices between South American and European countries. As a result, by focusing on the DCE approach, this study estimated the monetary amount that students from each country are willing to accept for each of the analysed job characteristics. Thus, this research fills a vacuum in the literature on student job preferences between three Latin speaking countries.

We take Cumulative Prospect Theory (CPT) seriously by rigorously estimating structural models using the full set of CPT parameters. Much of the literature only estimates a subset of CPT parameters, or more simply assumes CPT parameter values from prior studies. Our data are from laboratory experiments with undergraduate students and MBA students facing substantial real incentives and losses. We also estimate structural models from Expected Utility Theory (EUT), Dual Theory (DT), Rank-Dependent Utility (RDU), and Disappointment Aversion (DA) for comparison. Our major finding is that a majority of individuals in our sample locally asset integrate. That is, they see a loss frame for what it is, a frame, and behave as if they evaluate the net payment rather than the gross loss when one is presented to them. This finding is devastating to the direct application of CPT to these data for those subjects. Support for CPT is greater when losses are covered out of an earned endowment rather than house money, but RDU is still the best single characterization of individual and pooled choices. Defenders of the CPT model claim, correctly, that the CPT model exists “because the data says it should.” In other words, the CPT model was borne from a wide range of stylized facts culled from parts of the cognitive psychology literature. If one is to take the CPT model seriously and rigorously then it needs to do a much better job of explaining the data than we see here.

In this study, the authors examined demand-side credit in rural China with the aims of understanding attribute preferences and the willingness of farmers to pay for credit.

The authors implemented an in-the-field discrete choice experiment (DCE) using a D-optimal block (6 × 9 × 3) design applied to 420 farm households across five Chinese provinces (Shandong, Sichuan, Shaanxi, Jiangsu and Henan) in the summer and fall of 2018. The DCE included six attributes including the interest rate, term of loan, type of loan, type of repayment, type of institution and mobile banking services.

Conditional and mixed logit results indicated a downward sloping credit demand curve with variable elasticity across regions. Provincial willingness-to-pay (WTP) indicators suggested that farmers were willing to pay a premium for long-term ( 0.03–0.687%) and low collateral credit loans ( 0.79–2.93%). Also, four of five provinces indicated a preference for loan amortization rather than lump-sum payment. Interestingly, in comparison to the Agricultural Bank of China (ABC), only farmers in Shandong, Sichuan and Shaanxi indicated a preference for rural credit cooperatives (RCCs)/banks and the Postal Savings Bank of China (PSBC). Another quite surprising result was bank services, in our case, access to mobile banking did not appear to induce WTP for agricultural credit. While conditional and mixed logit regression coefficients were similar (and therefore robust), the authors found that there was substantial heterogeneity across attribute preferences on term of loan, type of loan and amortization. Preferences for type of lender and mobile banking were generally homogenous. This result alone suggested that lenders should consider offering a suite of credit products with different attributes in order to maximize the potential pool of borrowers. While there were some differences across provinces, farmers appeared to be indifferent to lenders, and it did not appear that offering banking services such as mobile banking had any bearing on credit decisions.

This paper presents a first step in using in-the-field choice experiments to better understand rural finance in China. Although the sample size satisfies conventional levels of significance and rank conditions, the authors caution against attributing results to China as a whole. Different provinces have different institutional structures and agricultural growing conditions and economies and these effects may differentially affect WTP for credit. Although by all indications farmers were aware of credit, not all farmers, in fact a minority, actually borrowed from a financial institution. This is not unusual in China, but for these farmers, the DCE was posed as hypothetical. Likewise, the study’s design was based on a generic credit product typical of rural China, and the authors caution against making inferences about other products with different attributes and risk structures.

This study is motivated by the rapidly changing dynamic in China's agricultural economy. With specific reference to new laws and regulations about the transfer of land use rights (LURs), China's agricultural economy is undergoing significant and rapid change which will require better understanding by policy makers, lenders and practitioners of the changing credit needs of farmers, including the new and emerging class of commercial farmers.

To the best of the authors’ knowledge, the authors believe that the result provided in this paper present the first use of in-the-field DCE and are the first to be reported in either the English or Chinese literature on rural credit product design.

This paper presents the results of a choice experiment carried out from August to October 2000 on the visitors of the Galleria Borghese Museum, a worldwide known heritage site located in Rome. The main objective of this work is to study the relevancy of choice experiment techniques as a tool aimed at measuring economic values and assessing user preferences concerning the multi‐attribute and multi‐value services as supplied by cultural institutions. A set of alternative incremental changes in service attributes showing improvements in supply are designed and presented to visitors. Alternative conditional logit specifications are used for analysing stated choices over the hypothetical incremental changes in museum attributes. Willingness to pay for incremental variations concerning site attributes is positive and statistically significant for most changes. Conditional logit specifications, which incorporate heterogeneity by adding interaction socio‐economic terms, are generally robust and do not violate the IIA assumption. In addition, in the present case study, non‐IIA models do not outperform conditional logit models. Choice experiments confirm as being a practical and effective tool for non‐market valuation, and they should be used to provide information to decision makers for justifying demand led policies.

This research measures the causal effects of pertinent agricultural credit policy attributes on farmers' participation probability and their willingness to pay (WTP) for agricultural credit and its associated services.

A randomized conjoint field experiment is conducted in three districts of Nangarhar Province, Afghanistan, capturing stated-preference data of 300 farmers. Each survey participant was provided with two hypothetical choices and one opt-out option to generate rankings based on their preferences. The levels of six attributes—namely, the credit service provider's location, the time required to obtain credit, the frequency of installments, the type of loan security, the provider of the credit services and the annual membership fee to participate in the proposed policy—are randomly assigned to produce the alternative choices.

The results reveal that farmers support the suggested agricultural credit services policy (ACSP), and the lower bound of their WTP for participation in the policy is as high as 5% of their average annual income.

This study provides evidence-based policy input for designing effective agricultural credit policies in Afghanistan, which can be extended to other countries with a similar context.

This is the first study estimating the causal effects of formal agricultural credit policy attributes on farmers' participation probability. Further, this study nonparametrically measures farmers' WTP for participation in the proposed policy.

The purpose of this paper is to investigate the demand for crop insurance. Moreover, farmer willingness to pay (WTP) for crop insurance was derived. Factors affecting the demand were also examined in a country where crop insurance products are not currently available. Sensitivity analysis was conducted by studying the price-anchoring effect.

Data from a choice experiment (CE) were analyzed with mixed logit models and the distribution of farmer WTP for crop insurance was derived. A split sample approach with varying premium vectors was used to analyze the price-anchoring effect.

Demand was revealed for crop insurance products in Finland. The demand was higher among younger farmers and farms with more arable land. WTP for crop insurance products was very sensitive to the premium interval presented in the CE design.

The price-anchoring effect may disrupt the market development of crop insurance products, because insurance companies may take advantage of the lack of awareness among farmers of crop insurance pricing.

The insurance product expected indemnity was a more important factor than the deductible in determining farmer WTP for crop insurance. Therefore, the 30 percent deductible level set for subsidized crop insurance products is not an obstacle for the development of such products in the EU.

The study applied a well-known method (CE) to crop insurance in a country where these products are non-existent. The split sample approach was used to examine the price-anchoring effect on crop insurance.