• Journal of Distribution Science
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• v.22 no.3
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• pp.59-70
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• 2024

Purpose: This study aimed to develop a strategic business conceptual model for large state plantations in West Java Province and Banten Province, Indonesia. The model was built through causal relationships and interrelationships between marketing strategies and business strategies that affect business performance on large state plantations. The plantation sector provides the largest contribution to gross domestic product and is an important part of national food distribution efforts. Research design, data, and methodology: This study used a literature review adapted from Pret and Logan (2019), which followed the guidelines of Tranfield et al. (2003), derived from the Scopus website with Q1/Q2 quartiles and inclusion/exclusion criteria published from 2012 to 2021. Results: Based on a systematic literature review approach, we constructed the strategic business conceptual model for large state plantations based on a combination of four causal and interrelationship variables that affect business performance, namely, industry attractiveness, unique capabilities, innovation management, and collaboration strategy. Conclusions: This research explains the relationship between industry attractiveness variables and unique capability as independent variables that can affect business performance through collaboration strategy and innovation management as intervening variables in the plantation sector, especially large state plantations, which have not been found in previous studies.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.119-126
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• 2008

Growth and yield prediction methods, ranging from whole-stand models to individual-tree models, have been developed for forest types managed for wood production. The resultant models are used for a host of purposes including inventory updating, management planning, evaluation of silvicultural alternatives, and harvest scheduling. Because of the large investment in developing growth and yield models for improved genotypes and silvicultural practices for loblolly pine (Pinus taeda) in the Southern United States, this region serves to illustrate approaches for modelling intensively managed forests. Analytical methods and computing power generally do not restrict development of reliable growth and yield models. However, long-term empirical observations on stand development, which are time consuming and expensive to obtain, often limit modelling efforts. Given that growth and yield models are used to project present volumes and to evaluate alternative treatment effects, data of both the inventory type and the experimental type are needed. Data for developing stand simulators for loblolly pine plantations have been obtained from a combination of permanent plots in operational forest stands and silvicultural experiments; these data collection efforts are described and summarized. Modelling is essential for integrating and synthesizing diverse information, identifying knowledge gaps, and making informed decisions. The questions being posed today are more complex than in the past, thus further accentuating the need for comprehensive models for stand development.