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The purpose of this paper is to measure technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from actual inefficiency using comprehensive household-level panel data.

This paper estimates technical efficiency based on the true random-effects stochastic production frontier estimator with a Mundlak adjustment. By utilising comprehensive panel data with 4,694 observations from 39 districts of four major maize-producing regions in Ethiopia, the author measures technical efficiency and examine its determinants while disentangling unobserved time-invariant heterogeneity from technical inefficiency. By using competing stochastic production frontier estimators, the author provides insights into the influence of farm heterogeneity on measuring farm efficiency and the subsequent impact on the ranking of farmers based on their efficiency scores.

The study results indicate that ignoring unobservable farmer heterogeneity leads to a downwards bias of technical efficiency estimates with a consequent effect on the ranking of farmers based on their efficiency scores. The mean technical efficiency score implied that about a 34% increase in maize productivity can be achieved with the current input use and technology in Ethiopia. The key determinants of the technical inefficiency of maize farmers are the age, gender and formal education level of the household head, household size, income, livestock ownership, and participation in off-farm activities.

While the findings of this study are critical for informing policy on improving agricultural production and productivity, a few important things are worth considering in terms of the generalisability of the findings. First, the study relied on secondary data, so only a snapshot of environmental factors was accounted for in the empirical estimations. Second, there could be other sources of unmeasured potential sources of heterogeneity caused by persistent technical inefficiency and endogeneity of inputs. Third, the study is limited to one country. Therefore, future research should extend the analysis to ensure the generalisability of the empirical findings regarding the extent to which unmeasured potential sources of heterogeneity caused by persistent technical inefficiency, endogeneity of inputs and other unobservable country-specific features – such as geographical differences.

This paper contributes to the literature on agricultural productivity and efficiency by providing new evidence on the influence of unobservable heterogeneity in a farm efficiency analysis. While agricultural production is characterised by heterogeneous production conditions, the influence of unobservable farm heterogeneity has generally been ignored in technical efficiency estimations, particularly in the context of smallholder farming. The value of this paper comes from disentailing producer-specific random heterogeneity from the actual inefficiency.

The aims of the paper are to evaluate the relevance of environmental factors (seasonality, size and quality) on hotels’ performance and benchmarks; to measure the bias in efficiency resulting from a failure to control for these sources of heterogeneity; and to propose some managerial policies to handle for environmental heterogeneity.

The sample is constituted by 2,705 hotels operating in Emilia-Romagna (Italy). The metafrontier approach is used to identify the different production processes and measure technical efficiency scores.

Different production processes exist among accommodation firms due to environmental features; not considering heterogeneity in technological sets produces high levels of bias in the efficiency measurement, albeit the ranking of hotels tends to be fairly consistent; the star rating is the primary source of efficiency bias followed by seasonality, while size has a minor impact.

Future research could be directed to analyse the relevance of environmental heterogeneity in other areas; study the dynamics; investigate agglomeration effects; and use other methodological tools.

The analysis proposes new managerial interventions: targeted strategies to different groups; creation of networks of enterprises, clustered mainly in respect to size for highly rated enterprises and seasonality for low-rated enterprises; and incentives to annual hotels and raise in the product quality.

This paper simultaneously considers several environmental factors affecting heterogeneity in hotel production processes; investigates the effect of heterogeneity on either the efficiency scores or the ranking of hotels; and focuses on micro, low-quality or seasonal hotels.

The purpose of this paper is to analyze the heterogeneity of regional grain production distribution in China, by examining the regional heterogeneity of absolute and relative changes in grain planting acreage, and explain it in terms of increasing labor costs and difficulties in agricultural inputs adjustment.

The study uses data from official statistical yearbooks and the satellite remote sensing image data of Landsat TM 30 m. Multivariate analysis is conducted to examine the effect of labor cost, difficulty in replacing agricultural input factors and other factors underpinning changes in grain acreage and grain structure adjustment.

The heterogeneity of changes in grain acreage and proportion of arable area for grain production are mainly determined using the labor cost and difficulties in the replacement of agricultural input factors.

To the best of the authors’ knowledge, this study is the first to systematically analyze the heterogeneity in restructuring grain production at provincial level and its causes. The results not only provide evidence of grain production restructuring at regional level, but also contribute to the understanding of the law of structural change in agricultural production.

The purpose of this paper is to compare two distinct network structures to determine and show which structure is more profitable. Specifically, it aims to show which factors render the lead factory concept advantageous.

Based on a simple, two‐stage model for prototype and serial production, the authors highlight factors that determine the relative advantages and disadvantages of the lead factory concept in comparison to an archetype network. The archetype network mirrors those networks that have not implemented special strategic plant roles.

The analysis shows that the lead factory concept benefits from an efficient knowledge transfer. Particularly, it is more profitable than the archetype network under the following conditions: there are a high number of production plants; the adaptation costs for implementing the transferred prototype from the lead factory to the plant are low; the manufacturing costs for the prototype are high; and the manufacturing processes are not highly specific or knowledge intensive.

The paper enables better understanding of the conditions under which the lead factory concept is advantageous for transferring knowledge within an intra‐firm network.

This study investigates how heterogeneity of product mix and production technology affects the use of responsibility accounting practices, the “unbundling” of products for cost management purposes, and the practice of increasing the number of expense accounts to create homogeneous cost pools. To test these relation‐ships, data were gathered from 31 Texas electric utilities. Analyses find that the more heterogeneous the products offered and the more diverse the production technologies employed, the greater the degree of product unbundling (subdividing products for the purposes of collecting and reporting costs), the more cost centers, and the greater the number of expense accounts.

In the context of carbon peaking and neutrality, effectively controlling agricultural carbon emissions has gained academic attention. As an essential form of agricultural service scale management, this study investigates whether and how trusteeship affects the carbon emission behavior in planting production.

The authors established a theoretical framework to analyze the impact of agricultural production trusteeship on carbon emissions from planting. China's provincial panel data in the 2012–2021 period were selected to test the impact, mechanisms and heterogeneity of agricultural production trusteeship on carbon emissions from planting using the bidirectional fixed effect model and the panel correction standard error regression model.

The findings indicate that agricultural production trusteeship significantly inhibits carbon emissions from planting, especially in the dimensions of fertilizer input, pesticide application, agricultural film use and mechanical fuel. Agricultural production trusteeship primarily affects the intensity of these carbon emissions through contiguous farmland management and planting structure adjustment. Further examinations revealed that the influence of agricultural production trusteeship on carbon emissions from planting was heterogeneous with respect to geographical location, proportion of non-farming income and scale of agricultural production.

This study is the first to systematically evaluate the impact of agricultural production trusteeship on carbon emissions from planting.

The purpose of this study is to analyze the environmental efficiency level and trend of the transportation sector in the upper–mid–downstream of the Yangtze River Economic Belt and the JingJinJi region in China and assess the effectiveness of policies for protecting the low-carbon environment.

This study uses the meta-frontier slack-based measure (SBM) approach to evaluate environmental efficiency, which targets and classifies specific regions into regional groups. First, this study employs the SBM with the undesirable outputs to construct the environmental efficiency measurement models of the four regions under the meta-frontier and group frontiers, respectively. Then, this study uses the technology gap ratio to evaluate the gap between the group frontier and the meta-frontier.

The analysis reveals several key findings: (1) the JingJinJi region and the downstream of the YEB had achieved the overall optimal production technology in transportation than the other two regions; (2) significant technology gaps in environmental efficiency were observed among these four regions in China; and (3) the downstream region of the YEB exhibited the lowest levels of energy consumption and excessive CO₂ emissions.

To evaluate the differences in environmental efficiency resulting from regions and technological gaps in transportation, this study employs the meta-frontier model, which overcomes the limitation of traditional environmental efficiency methods. Furthermore, in the practical, the study provides the advantage of observing the disparities in transportation efficiency performed by the Yangtze River Economic Belt and the Beijing–Tianjin–Hebei regions.

This study examines the nature of the researchers’ perspectives used in analytical and empirical cost system research published in the 1990s in an attempt to better understand current cost system research. The conceptual framework used for the evaluation is based on the research perspectives that have influenced the selection of different approaches in cost system research in the last three decades and reflects assumptions made in the research models and useful empirical implications.

The taxonomy used in the paper deepens our understanding of current cost accounting research and is argued as relevant on the premise that researchers would certainly care about finding a “better” cost system. A “better” system is defined in this study as the system that would lead to changes in decisions resulting in payoffs that are greater than the costs of implementing the new system.

This study examines the performance of India's food processing sector by estimating its output growth, technical efficiency (TE) and input-driven growth (IDG)

This study used panel data from six food processing manufacturing industries for the period 2000–01 to 2017–18. Technical efficiency and input-driven growth was measured using the parametric half-normal stochastic frontier production function.

The findings of this study showed that the estimated average technical efficiency is 86.6%, which specifies that the Indian food processing sector is technically inefficient. In addition, the output growth rate is 5.5%, driven by high doses of inputs (5.7%), whereas there is no indication of constant returns to scale. However, the food processing sector has experienced more input-driven expansion than either technological or efficiency changes.

This study is limited to India's organized manufacturing food processing sector; the aggregate macro data at a three-digit level based on the national industrial classification (NIC) was used. This study provides robust estimates for industrialists and processors, as well as concrete policy formulations on how overdoses of inputs may lead to high exploitation of resources, whereas outputs can be augmented by implementing upgraded and new technologies.

Previous research has estimated the total factor productivity and technical efficiency only in order to analyze the food sector's performance, but none of the studies have evaluated the share of inputs in growth performance and efficiency. Therefore, this study contributes by measuring growth performance and the share of inputs in the growth performance of India's food processing sector.

The purpose of this paper is to revisit causal effects and investigate hysteresis effects of lean production on performance. With a focus on firm heterogeneity, this paper explores the role of organization ownership structure in shaping the relationship between lean production and performance.

The propensity score matching (PSM) model combined with difference-in-difference (DID) estimation is applied to minimize selection bias caused by firm heterogeneity and endogeneity problems derived from unobserved fixed variables that could potentially affect the desired causal relationship.

Results show that lean production has no significant effect on business performance; however, the relationship between lean production and operations performance is positive and significant, especially for non-state-owned firms. Furthermore, the non-significant effect of lean production on performance of state-owned firms is largely due to the failure of lean production implementation. Meanwhile, lean production can only improve operations performance of non-state-owned firms in the short term due to their inability to continuously implement lean production.

This paper only covers manufacturing listed firms in China. Further studies are needed to test the wide implications of this paper in other countries.

This paper may help managers to identify problems in the implementation of lean production for different organization ownership structure firms, thus providing new insight into the implementation of lean production.

This paper appears to be the first one to examine causal effects of lean production on performance in China by applying the PSM model combined with DID estimation.