This paper presents a new coding scheme called semi-low-density parity-check convolutional code (semi-LDPC-CC), whose parity-check matrix consists of both sparse and dense sub-matrices, a feature distinguished from the conventional LDPC-CCs. We propose sliding-window list (SWL) decoding algorithms with a fixed window size of two, resulting in a low decoding latency but a competitive error-correcting performance. The performance can be predicted by upper bounds derived from the first event error probability and by genie-aided (GA) lower bounds estimated from the underlying LDPC block codes (LDPC-BCs), while the complexity can be reduced by truncating the list with a threshold on the difference between the soft metrics in the serial decoding implementation. Numerical results are presented to validate our analysis and demonstrate the performance advantage of the semi-LDPC-CCs over the conventional LDPC-CCs.