Determinant of Indonesian Plantation Industry Investment ERA 4.0

2021 ◽  
Vol 8 (1) ◽  
pp. 1-13
Author(s):  
M Noor Salim ◽  
Darwati Susilastuti ◽  
Wahyu Murti
Keyword(s):  
2018 ◽  
Vol 16 (1) ◽  
pp. 13
Author(s):  
Isril ' ◽  
Rury Febrina

The development dynamics of Pekanbaru City is so rapid and accompanied by rapid populationgrowth has brought consequences on increasing the volume of waste from the community. Therapid growth of population, industry, investment and trade in Pekanbaru City produces domesticwaste of approximately 1,100 tons per day. With the amount of waste generated in such a way, theenvironmental conditions of Pekanbaru City, especially the community settlements, fall into thecategory of complex hygiene issues. The Waste Management consisting of Planning, Organizing,Staffing, Motivating, and Supervision/Controlling.


2008 ◽  
Author(s):  
Scot A. Arnold ◽  
Karen W. Tyson ◽  
Benjamin S. Aronin

2012 ◽  
Vol 7 (14) ◽  
pp. 511-520
Author(s):  
Jie TANG ◽  
Lili ZHANG ◽  
Zhongying QI ◽  
Pingping Fu

2019 ◽  
Vol 97 (Supplement_1) ◽  
pp. 11-11
Author(s):  
Emily E Ridge ◽  
Ron Gill ◽  
Courtney L Daigle

Abstract A survey was administered to Texas cattle feedyard employees (n = 111) from 31 different operations measuring stockperson perception, job satisfaction and socioeconomic status using Likert statements and multiple-choice questions. Differences among employment roles (manager, pen rider, processor, doctor) were evaluated using a Kruskal-Wallis test followed by a Multiple Comparison procedure. Managers more strongly agreed that “beef cattle are not dirty” than doctors (P = 0.03) and that “cattle behavior is affected by the way we treat them” than pen riders (P = 0.002) or processors (P = 0.01). Managers were less likely than doctors, pen riders, and processors to believe they have too many cattle to look after (P = 0.05, P = 0.006 and P = 0.01, respectively). Pen riders reported less confidence in performing euthanasia than doctors (P = 0.02) and managers (P = 0.02), and, along with processors, agreed that cattle were not always euthanized in a timely manner (P = 0.02 and P = 0.02, respectively). While all roles viewed Holstein cattle unfavorably (P < 0.001), processors viewed them more positively than pen riders (P = 0.05) and managers (P = 0.001). Socioeconomic results showed that Texas feedyards have a dedicated, passionate work force, with 43% of participants having worked in the industry for 9+ years and 49% of participants working at cattle feedyards because they enjoy working with animals. Unfortunately, it was evident that stockpeople are underpaid (57% of participants making between $10–15/hr) and overworked (76% of participants working 50+ hrs/wk). Survey responses identified critical role-dependent knowledge gaps and biases. A disconnect was observed among compensation, workload, and the duration of time stockpeople spend interacting with cattle. Increasing industry investment in feedyard employees and providing breed-specific and employee role-specific education may promote an encouraging workplace that ensures cattle experience good welfare.


2012 ◽  
Vol 09 (02) ◽  
pp. 1250011
Author(s):  
MARTIN KAGGWA ◽  
JASPER L. STEYN ◽  
ANASTASSIOS POURIS

Investment in state of the art machinery and tooling and in R&D is widely seen as a prerequisite for achieving industry competitiveness in the long term. Investment-based incentives that countries provide for these inputs are perceived as a way of supporting industry competitiveness. Despite this being a global phenomenon, there is no formal process to guide the offer of these incentives. The process of designing such incentives is often based on internalized judgment rather than on formal models making it difficult to assess such interventions objectively and to improve on them. Specific to South Africa, the offer of incentives to the automotive industry to support its competitiveness has had mixed results. In particular, investment in R&D has remained minimal. The paper presents a system dynamics model as a proposed instrument in formalizing the offer of incentives, applied to the South African government's offer of incentives to the automotive manufacturing sector. The model was developed from qualitative and quantitative information on how the incentives had been structured. Simulations of the model reveal that the incentives model, as a stand-alone intervention, had a significant and positive effect on industry investment, but had no specific policy lever to direct investment into R&D and subsequent innovative activities. By this measure, the incentives model has not been a strong policy framework for supporting long-term industry competitiveness.


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